Starting Dynare (version 6.4).
Calling Dynare with arguments: none
Starting preprocessing of the model file ... 
Found 16 equation(s). 
Evaluating expressions... 
Computing static model derivatives (order 1). 
Normalizing the static model... 
Finding the optimal block decomposition of the static model... 
7 block(s) found: 
  5 recursive block(s) and 2 simultaneous block(s). 
  the largest simultaneous block has 9 equation(s) 
                                 and 9 feedback variable(s). 
Computing dynamic model derivatives (order 2). 
Normalizing the dynamic model... 
Finding the optimal block decomposition of the dynamic model... 
3 block(s) found: 
  1 recursive block(s) and 2 simultaneous block(s). 
  the largest simultaneous block has 9 equation(s) 
                                 and 7 feedback variable(s). 
Preprocessing completed. 
Preprocessing time: 0h00m00s.
Initial value of the log posterior (or likelihood): -85215.7638
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.684400e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 97)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',97,0)">line 97</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Gradient norm  16584586.8477
Minimum Hessian eigenvalue 1.7331e-08
Maximum Hessian eigenvalue 11111518556046.17
 
Iteration 1
Correct for low angle: 2.31562e-10
Predicted improvement: 13730823744947.044921875
lambda =          1; f = 109674071578502528.0000000
lambda =    0.33333; f = 12186007485072618.0000000
lambda =    0.11111; f = 1354000675693806.2500000
lambda =   0.037037; f = 150444467578401.8125000
lambda =   0.012346; f = 16716034689289.6054688
lambda =  0.0041152; f = 1857331483587.9968262
lambda =  0.0013717; f = 206368313984.0337524
lambda = 0.00045725; f =  22929246218.6193199
lambda = 0.00015242; f =   2547555713.8745456
lambda = 5.0805e-05; f =    283066147.0268577
lambda = 1.6935e-05; f =     31503765.4177043
lambda =  5.645e-06; f =      3568246.3841430
lambda = 1.8817e-06; f =       469585.3915629
lambda = 6.2723e-07; f =       127051.5758235
lambda = 2.0908e-07; f =        89579.5420340
lambda = 6.9692e-08; f =        85611.7414542
lambda = 2.3231e-08; f =        85236.1275399
lambda = 7.7435e-09; f =        18061.3226432
Norm of dx 3.3117e+08
Predicted improvement: 137524260454035.875000000
lambda =          1; f = 3076317207432.0761719
lambda =    0.33333; f = 341812931098.3952637
lambda =    0.11111; f =  37979234421.8274002
lambda =   0.037037; f =   4219972059.4151211
lambda =   0.012346; f =    468955330.8084734
lambda =  0.0041152; f =     52179835.2207881
lambda =  0.0013717; f =      5872827.1302113
lambda = 0.00045725; f =       728064.1117210
lambda = 0.00015242; f =       156577.1438949
lambda = 5.0805e-05; f =        93125.8447562
lambda = 1.6935e-05; f =        86089.1498504
lambda =  5.645e-06; f =        85311.3013005
lambda = 1.8817e-06; f =        85225.9549603
lambda = 6.2723e-07; f =        85216.7662207
lambda = 2.0908e-07; f =        85215.8425517
lambda = 6.9692e-08; f =        85215.7678330
lambda = 2.3231e-08; f =        85215.7638638
lambda = 7.7435e-09; f =         1322.0081131
lambda = 2.5812e-09; f =         3617.6633589
Norm of dx 1.6585e+07
Gradient step!!
Predicted improvement:      330.736590602
lambda =          1; f =          889.0137306
Norm of dx  0.0045492
Done for param e_a =   0.0185; f = 889.0137
Predicted improvement:       72.769713915
lambda =          1; f =          794.5158145
Norm of dx    0.04581
Done for param e_v =   0.1962; f = 794.5158
Predicted improvement:       12.996985627
lambda =          1; f =          769.5812090
lambda =     1.9332; f =          748.0976930
lambda =     3.7372; f =          710.8602415
lambda =     7.2247; f =          651.9713175
lambda =     13.967; f =          572.2699259
Norm of dx 0.00030866
Done for param e_g =   0.0158; f = 572.2699
Near-singular H problem.
Correct for low angle: 1.05078e-11
Predicted improvement: 22642201197609424.000000000
lambda =          1; f = 226422011439179219599360.0000000
lambda =    0.33333; f = 25158001151705469681664.0000000
lambda =    0.11111; f = 2795333421529123258368.0000000
lambda =   0.037037; f = 310592589134963998720.0000000
lambda =   0.012346; f = 34510283262609293312.0000000
lambda =  0.0041152; f = 3834474445050147328.0000000
lambda =  0.0013717; f = 426052225111071424.0000000
lambda = 0.00045725; f = 47338972455154368.0000000
lambda = 0.00015242; f = 5259831272490259.0000000
lambda = 5.0805e-05; f = 584407511895739.1250000
lambda = 1.6935e-05; f = 64928106544993.0703125
lambda =  5.645e-06; f = 7212213818532.6318359
lambda = 1.8817e-06; f = 800683916059.3325195
lambda = 6.2723e-07; f =  88740727051.2171173
lambda = 2.0908e-07; f =   9785602398.4730148
lambda = 6.9692e-08; f =   1062702145.7021303
lambda = 2.3231e-08; f =    110121464.9426304
lambda = 7.7435e-09; f =      9822653.2262189
lambda = 2.5812e-09; f =       526169.5285361

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =  89077169398.6505432
lambda = -2.0908e-07; f =   9897537649.6476765
lambda = -6.9692e-08; f =   1099801698.1238797
lambda = -2.3231e-08; f =    122275784.4467445
lambda = -7.7435e-09; f =     13661895.0911210
lambda = -2.5812e-09; f =      1593718.8470341
Norm of dx 4.7584e+11
Done for param e_rer =   0.0115; f = 572.2699
Predicted improvement:        0.031822369
lambda =          1; f =          572.2393683
Norm of dx 0.00022517
Done for param e_yw =   0.0098; f = 572.2394
Predicted improvement:        0.337248950
lambda =          1; f =          571.5659441
lambda =     1.9332; f =          570.9394502
lambda =     3.7372; f =          569.7335998
lambda =     7.2247; f =          567.4220953
lambda =     13.967; f =          563.0261868
lambda =         27; f =          554.7947325
lambda =     52.196; f =          539.8443085
lambda =      100.9; f =          514.3096089
lambda =     195.07; f =          476.0696785
lambda =      377.1; f =          435.4610344
Norm of dx 0.00012179
Done for param alp =   0.2768; f = 435.4610
Predicted improvement:        0.134879805
lambda =          1; f =          435.1919337
lambda =     1.9332; f =          434.9420005
lambda =     3.7372; f =          434.4620708
lambda =     7.2247; f =          433.5462989
lambda =     13.967; f =          431.8203265
lambda =         27; f =          428.6457751
lambda =     52.196; f =          423.0883663
lambda =      100.9; f =          414.3393460
lambda =     195.07; f =          403.8486180
Norm of dx  7.702e-05
Done for param bet =   0.9175; f = 403.8486
Predicted improvement:        0.027145440
lambda =          1; f =          403.7945142
lambda =     1.9332; f =          403.7443628
lambda =     3.7372; f =          403.6483342
lambda =     7.2247; f =          403.4661433
lambda =     13.967; f =          403.1268275
lambda =         27; f =          402.5190434
lambda =     52.196; f =          401.5240836
lambda =      100.9; f =          400.2730331
Norm of dx 1.9166e-05
Done for param delt =   0.0981; f = 400.2730
Predicted improvement:        0.000705310
lambda =          1; f =          400.2716225
lambda =     1.9332; f =          400.2703061
lambda =     3.7372; f =          400.2677615
lambda =     7.2247; f =          400.2628425
lambda =     13.967; f =          400.2533342
lambda =         27; f =          400.2349564
lambda =     52.196; f =          400.1994420
lambda =      100.9; f =          400.1308359
lambda =     195.07; f =          399.9983933
lambda =      377.1; f =          399.7430518
lambda =        729; f =          399.2520308
lambda =     1409.3; f =          398.3125600
lambda =     2724.4; f =          396.5332018
lambda =     5266.8; f =          393.2334262
lambda =      10182; f =          387.3976406
lambda =      19683; f =          378.3248994
lambda =      38051; f =          371.1692986
Norm of dx 5.9802e-06
Done for param sig =   1.7721; f = 371.1693
Predicted improvement:        0.000087515
lambda =          1; f =          371.1691236
lambda =     1.9332; f =          371.1689603
lambda =     3.7372; f =          371.1686446
lambda =     7.2247; f =          371.1680344
lambda =     13.967; f =          371.1668550
lambda =         27; f =          371.1645764
lambda =     52.196; f =          371.1601759
lambda =      100.9; f =          371.1516863
lambda =     195.07; f =          371.1353384
lambda =      377.1; f =          371.1039753
lambda =        729; f =          371.0442427
lambda =     1409.3; f =          370.9321315
lambda =     2724.4; f =          370.7280099
lambda =     5266.8; f =          370.3808586
lambda =      10182; f =          369.8897363
lambda =      19683; f =          369.6363424
Norm of dx 3.3518e-06
Done for param phi1 =   1.5662; f = 369.6363
Predicted improvement:        0.000384846
lambda =          1; f =          369.6355727
lambda =     1.9332; f =          369.6348544
lambda =     3.7372; f =          369.6334659
lambda =     7.2247; f =          369.6307816
lambda =     13.967; f =          369.6255926
lambda =         27; f =          369.6155617
lambda =     52.196; f =          369.5961718
lambda =      100.9; f =          369.5586937
lambda =     195.07; f =          369.4862649
lambda =      377.1; f =          369.3463333
lambda =        729; f =          369.0761429
lambda =     1409.3; f =          368.5550227
lambda =     2724.4; f =          367.5521160
lambda =     5266.8; f =          365.6302001
lambda =      10182; f =          361.9780202
lambda =      19683; f =          355.1549775
lambda =      38051; f =          342.8591077
lambda =      73559; f =          322.4941067
lambda =  1.422e+05; f =          296.4740887
Norm of dx 1.6866e-05
Done for param phi2 =   3.2013; f = 296.4741
Predicted improvement:       13.152584919
lambda =          1; f =          283.3215015
Norm of dx     2.5644
Done for param psi1 =   1.4000; f = 283.3215
Predicted improvement:        0.060942080
lambda =          1; f =          283.2001182
lambda =     1.9332; f =          283.0877495
lambda =     3.7372; f =          282.8729969
lambda =     7.2247; f =          282.4671085
lambda =     13.967; f =          281.7171878
lambda =         27; f =          280.3981262
lambda =     52.196; f =          278.3447217
lambda =      100.9; f =          276.3243428
Norm of dx 0.00028953
Done for param hf =   0.4706; f = 276.3243
Predicted improvement:        0.000696107
lambda =          1; f =          276.3229507
lambda =     1.9332; f =          276.3216517
lambda =     3.7372; f =          276.3191409
lambda =     7.2247; f =          276.3142883
lambda =     13.967; f =          276.3049123
lambda =         27; f =          276.2868052
lambda =     52.196; f =          276.2518693
lambda =      100.9; f =          276.1845879
lambda =     195.07; f =          276.0554761
lambda =      377.1; f =          275.8094395
lambda =        729; f =          275.3470427
lambda =     1409.3; f =          274.5021484
lambda =     2724.4; f =          273.0489796
lambda =     5266.8; f =          270.8963773
lambda =      10182; f =          269.1202868
Norm of dx 1.3065e-05
Done for param rhoa =   0.5666; f = 269.1203
Predicted improvement:        0.000100414
lambda =          1; f =          269.1200859
lambda =     1.9332; f =          269.1198986
lambda =     3.7372; f =          269.1195363
lambda =     7.2247; f =          269.1188361
lambda =     13.967; f =          269.1174826
lambda =         27; f =          269.1148670
lambda =     52.196; f =          269.1098136
lambda =      100.9; f =          269.1000558
lambda =     195.07; f =          269.0812350
lambda =      377.1; f =          269.0450100
lambda =        729; f =          268.9755719
lambda =     1409.3; f =          268.8435223
lambda =     2724.4; f =          268.5962546
lambda =     5266.8; f =          268.1470336
lambda =      10182; f =          267.3786977
lambda =      19683; f =          266.2213610
lambda =      38051; f =          264.9632772
Norm of dx  4.203e-06
Done for param rhov =   0.3391; f = 264.9633
Predicted improvement:        0.030689481
lambda =          1; f =          264.9021338
lambda =     1.9332; f =          264.8455007
lambda =     3.7372; f =          264.7371814
lambda =     7.2247; f =          264.5321251
lambda =     13.967; f =          264.1519481
lambda =         27; f =          263.4776436
lambda =     52.196; f =          262.4005803
lambda =      100.9; f =          261.1637748
Norm of dx 0.00091299
Done for param rhog =   0.5921; f = 261.1638
Predicted improvement:       29.259303883
lambda =          1; f =          205.9276102
lambda =     1.9332; f =          160.3023642
lambda =     3.7372; f =           88.2943054
lambda =     7.2247; f =            9.4596029
Norm of dx   0.077752
Done for param rhorer =   0.5617; f =   9.4596
Predicted improvement:        0.000049738
lambda =          1; f =            9.4595482
Norm of dx 0.00069564
Done for param rhoyw =   0.5507; f =   9.4595
Sequence of univariate steps!!
Actual dxnorm 2.4934
FVAL          9.4595
Improvement   85206.3043
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.166407e-17.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.78644 s.
 
Iteration 2
Correct for low angle: 3.52513e-11
Predicted improvement: 4441198413.492752075
lambda =          1; f = 936323120903728.0000000
lambda =    0.33333; f = 104035859066215.5156250
lambda =    0.11111; f = 11559525477451.7246094
lambda =   0.037037; f = 1284386913464.5788574
lambda =   0.012346; f = 142708054979.8842468
lambda =  0.0041152; f =  15855916541.3596344
lambda =  0.0013717; f =   1761590512.5147738
lambda = 0.00045725; f =    195672960.1293315
lambda = 0.00015242; f =     21721678.6020949
lambda = 5.0805e-05; f =      2406944.3079691
lambda = 1.6935e-05; f =       265258.0115887
lambda =  5.645e-06; f =        28757.9648316
lambda = 1.8817e-06; f =         2968.5476204
lambda = 6.2723e-07; f =          265.8454064
lambda = 2.0908e-07; f =           19.8080228
lambda = 6.9692e-08; f =         -302.6001105
Norm of dx   3.06e+07
Predicted improvement: 1685250641.523064375
lambda =          1; f =        31974.0033291
lambda =    0.33333; f =         3495.7477923
lambda =    0.11111; f =          375.9843168
lambda =   0.037037; f =           44.0677619
lambda =   0.012346; f =           11.6406059
lambda =  0.0041152; f =            9.4598399
lambda =  0.0013717; f =           76.6127052
lambda = 0.00045725; f =           16.3350562
lambda = 0.00015242; f =           10.0503919
lambda = 5.0805e-05; f =            9.4897133
lambda = 1.6935e-05; f =            9.4597326
lambda =  5.645e-06; f =         -363.9510593
lambda = 1.8817e-06; f =         -461.2755972
lambda = 6.2723e-07; f =         -475.5459173
lambda = 2.0908e-07; f =         -415.2233174
lambda = 6.9692e-08; f =         -353.7546017
lambda = 2.3231e-08; f =         -321.8366243
lambda = 7.7435e-09; f =         -309.2922945
lambda = 2.5812e-09; f =         -304.8635617
Norm of dx      58056
Gradient step!!
Predicted improvement:        0.310821816
lambda =          1; f =         -476.1459374
lambda =     1.9332; f =         -476.6682169
lambda =     3.7372; f =         -477.5816107
lambda =     7.2247; f =         -479.0253407
lambda =     13.967; f =         -480.8377330
Norm of dx 0.00053984
Done for param e_a =   0.0509; f = -480.8377
Predicted improvement:        0.034358152
lambda =          1; f =         -480.8706946
Norm of dx  0.0045873
Done for param e_v =   0.1916; f = -480.8707
Predicted improvement:        1.009848285
lambda =          1; f =         -482.4085806
lambda =     1.9332; f =         -483.1287072
Norm of dx  0.0021095
Done for param e_g =   0.0344; f = -483.1287
Predicted improvement:        0.043428269
lambda =          1; f =         -483.2154643
lambda =     1.9332; f =         -483.2962429
lambda =     3.7372; f =         -483.4518924
lambda =     7.2247; f =         -483.7508001
lambda =     13.967; f =         -484.3205650
lambda =         27; f =         -485.3867526
lambda =     52.196; f =         -487.2714084
lambda =      100.9; f =         -489.7717261
lambda =     195.07; f =         -481.4935896
lambda =     131.35; f =         -489.9151457
Norm of dx 0.00012222
Done for param e_rer =   0.0323; f = -489.9151
Predicted improvement:       31.025777186
lambda =          1; f =         -537.2655632
lambda =     1.9332; f =         -564.9002708
Norm of dx    0.02297
Done for param alp =   0.3243; f = -564.9003
Near-singular H problem.
Correct for low angle: 6.54452e-10
Predicted improvement: 5836936153649.934570312
lambda =          1; f = 58369361535449972736.0000000
lambda =    0.33333; f = 6485484614816799744.0000000
lambda =    0.11111; f = 720609401568578816.0000000
lambda =   0.037037; f = 80067711259486880.0000000
lambda =   0.012346; f = 8896412353528301.0000000
lambda =  0.0041152; f = 988490258624179.7500000
lambda =  0.0013717; f = 109832249998592.8750000
lambda = 0.00045725; f = 12203583013299.5000000
lambda = 0.00015242; f = 1355953561524.1694336
lambda = 5.0805e-05; f = 150661471301.5539551
lambda = 1.6935e-05; f =  16740151638.7372742
lambda =  5.645e-06; f =   1860012907.9526482
lambda = 1.8817e-06; f =    206666792.8934349
lambda = 6.2723e-07; f =     22962546.5998817
lambda = 2.0908e-07; f =      2551256.2123475
lambda = 6.9692e-08; f =       283432.5695009
lambda = 2.3231e-08; f =        31484.6685148
lambda = 7.7435e-09; f =         3501.2918857
lambda = 2.5812e-09; f =          395.6393463

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     22963000.4397821
lambda = -2.0908e-07; f =      2551407.4894730
lambda = -6.9692e-08; f =       283482.9923681
lambda = -2.3231e-08; f =        31501.4732960
lambda = -7.7435e-09; f =         3506.8906381
lambda = -2.5812e-09; f =          397.5027558
Norm of dx   7.64e+09
Done for param bet =   0.9213; f = -564.9003
Predicted improvement:        0.080503417
lambda =          1; f =         -564.9801986
Norm of dx 0.00040118
Done for param delt =   0.0995; f = -564.9802
Predicted improvement:       37.990345949
lambda =          1; f =         -592.9779740
Norm of dx    0.53818
Done for param sig =   2.3105; f = -592.9780
Predicted improvement:        1.256931016
lambda =          1; f =         -594.5864306
Norm of dx   0.098839
Done for param phi1 =   1.4672; f = -594.5864
Predicted improvement:        0.763087158
lambda =          1; f =         -595.4145034
Norm of dx    0.30325
Done for param phi2 =   2.8981; f = -595.4145
Predicted improvement:        9.095327953
lambda =          1; f =         -604.5098315
Norm of dx     2.1325
Done for param psi1 =   1.4000; f = -604.5098
Predicted improvement:        0.209380151
lambda =          1; f =         -604.7271494
Norm of dx   0.013856
Done for param hf =   0.4568; f = -604.7271
Predicted improvement:        0.334436491
lambda =          1; f =         -605.0652356
Norm of dx   0.061704
Done for param rhoa =   0.5049; f = -605.0652
Predicted improvement:        1.488487680
lambda =          1; f =         -606.7158728
Norm of dx     0.1045
Done for param rhov =   0.2346; f = -606.7159
Predicted improvement:        0.003277482
lambda =          1; f =         -606.7191382
Norm of dx  0.0057757
Done for param rhog =   0.5979; f = -606.7191
Predicted improvement:        1.185293639
lambda =          1; f =         -607.6393735
Norm of dx    0.14211
Done for param rhorer =   0.7040; f = -607.6394
Predicted improvement:        0.000404137
lambda =          1; f =         -607.6397775
Norm of dx  0.0020852
Done for param rhoyw =   0.5528; f = -607.6398
Sequence of univariate steps!!
Actual dxnorm 0.65648
FVAL          -607.6398
Improvement   617.0993
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.043361e-18.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.3411 s.
 
Iteration 3
Correct for low angle: 4.88244e-11
Predicted improvement: 2786102247.067492962
lambda =          1; f =   2629004611.3025627
lambda =    0.33333; f =    292078345.0752230
lambda =    0.11111; f =     32441699.4316342
lambda =   0.037037; f =      3600459.3762370
lambda =   0.012346; f =       398302.5236008
lambda =  0.0041152; f =        43315.7763328
lambda =  0.0013717; f =         4142.1369181
lambda = 0.00045725; f =         -120.7702536
lambda = 0.00015242; f =         -564.8222249
lambda = 5.0805e-05; f =         -605.6188472
lambda = 1.6935e-05; f =         -607.6331408
lambda =  5.645e-06; f =         -607.6393189
lambda = 1.8817e-06; f =         -607.6397755
lambda = 6.2723e-07; f =       176066.3638903
lambda = 2.0908e-07; f =        18433.1050347
lambda = 6.9692e-08; f =         1317.4298851
lambda = 2.3231e-08; f =         -451.2708572
lambda = 7.7435e-09; f =         -603.4462741
lambda = 2.5812e-09; f =         -610.3890400
Norm of dx 6.7521e+08
Predicted improvement:  1362107.412590020
lambda =          1; f =          -46.7686634
lambda =    0.33333; f =         -557.5514295
lambda =    0.11111; f =         -605.0883280
lambda =   0.037037; f =         -607.6320838
lambda =   0.012346; f =         -607.6392249
lambda =  0.0041152; f =         -607.6397730
lambda =  0.0013717; f =         -607.3771674
lambda = 0.00045725; f =         -607.6226089
lambda = 0.00015242; f =         -607.6385116
lambda = 5.0805e-05; f =         -607.6397101
lambda = 1.6935e-05; f =         -595.8539438
lambda =  5.645e-06; f =         -610.9927783
lambda = 1.8817e-06; f =         -611.4054815
lambda = 6.2723e-07; f =         -610.8307213
lambda = 2.0908e-07; f =         -610.5482402
lambda = 6.9692e-08; f =         -610.4434585
lambda = 2.3231e-08; f =         -610.4073305
lambda = 7.7435e-09; f =         -610.3951536
lambda = 2.5812e-09; f =         -610.3910797
Norm of dx     1650.5
Gradient step!!
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.545333e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 175)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',175,0)">line 175</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Correct for low angle: 6.96153e-11
Predicted improvement: 1808783570.700873137
lambda =          1; f =   1096313953.8281555
lambda =    0.33333; f =    121790882.9991962
lambda =    0.11111; f =     13524703.6002510
lambda =   0.037037; f =      1499848.7129035
lambda =   0.012346; f =       165327.2592285
lambda =  0.0041152; f =        17571.5699393
lambda =  0.0013717; f =         1328.9359313
lambda = 0.00045725; f =         -417.5930408
lambda = 0.00015242; f =         -593.1601871
lambda = 5.0805e-05; f =         -607.3765975
lambda = 1.6935e-05; f =     55087817.9173710
lambda =  5.645e-06; f =      6115585.8997361
lambda = 1.8817e-06; f =       677389.7803275
lambda = 6.2723e-07; f =        74200.0982806
lambda = 2.0908e-07; f =         7530.4618291
lambda = 6.9692e-08; f =          239.8635136
lambda = 2.3231e-08; f =         -531.1576753
lambda = 7.7435e-09; f =         -603.8116074
lambda = 2.5812e-09; f =         -600.6977231

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =        72307.0826892
lambda = -2.0908e-07; f =         6913.8562832
lambda = -6.9692e-08; f =           49.0711623
lambda = -2.3231e-08; f =         -579.9747644
lambda = -7.7435e-09; f =         -591.0215201
lambda = -2.5812e-09; f =         -614.1427638
Norm of dx 4.3836e+08
Predicted improvement:        2.409809701
lambda =          1; f =         -616.9667780
Norm of dx  0.0078504
Done for param e_a =   0.0622; f = -616.9668
Predicted improvement:        2.730522346
lambda =          1; f =         -620.1998211
Norm of dx   0.028915
Done for param e_v =   0.2212; f = -620.1998
Predicted improvement:        0.995201730
lambda =          1; f =         -621.3191560
Norm of dx  0.0040052
Done for param e_g =   0.0430; f = -621.3192
Predicted improvement:        0.175305605
lambda =          1; f =         -621.5075657
Norm of dx  0.0016016
Done for param e_rer =   0.0355; f = -621.5076
Predicted improvement:        0.000196723
lambda =          1; f =         -621.5077630
Norm of dx 1.6694e-05
Done for param e_yw =   0.0098; f = -621.5078
Predicted improvement:        5.225950973
lambda =          1; f =         -626.0880102
Norm of dx   0.024779
Done for param alp =   0.3499; f = -626.0880
Predicted improvement:        0.098990665
lambda =          1; f =         -626.1899702
Norm of dx  0.0016465
Done for param bet =   0.9207; f = -626.1900
Predicted improvement:        0.300253676
lambda =          1; f =         -626.4902222
Norm of dx 0.00077243
Done for param delt =   0.0997; f = -626.4902
Predicted improvement:        0.871512538
lambda =          1; f =         -627.3560119
Norm of dx   0.090921
Done for param sig =   2.2195; f = -627.3560
Predicted improvement:        1.014428776
lambda =          1; f =         -628.3320990
Norm of dx    0.10832
Done for param phi1 =   1.3588; f = -628.3321
Predicted improvement:        0.266853925
lambda =          1; f =         -628.6013935
Norm of dx    0.18652
Done for param phi2 =   3.0846; f = -628.6014
Predicted improvement:        0.747504495
lambda =          1; f =         -629.3488980
Norm of dx    0.61135
Done for param psi1 =   1.4000; f = -629.3489
Predicted improvement:        0.326386809
lambda =          1; f =         -629.6553884
Norm of dx   0.020349
Done for param hf =   0.4772; f = -629.6554
Predicted improvement:        0.356244310
lambda =          1; f =         -630.0126483
Norm of dx   0.068992
Done for param rhoa =   0.4359; f = -630.0126
Predicted improvement:        0.013530755
lambda =          1; f =         -630.0260892
Norm of dx   0.012097
Done for param rhov =   0.2467; f = -630.0261
Predicted improvement:        0.037996226
lambda =          1; f =         -630.0642408
Norm of dx   0.021886
Done for param rhog =   0.5760; f = -630.0642
Predicted improvement:        0.436167364
lambda =          1; f =         -630.5009705
Norm of dx   0.077945
Done for param rhorer =   0.6260; f = -630.5010
Sequence of univariate steps!!
Actual dxnorm 0.26161
FVAL          -630.501
Improvement   22.8612
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.217285e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.34712 s.
 
Iteration 4
Correct for low angle: 8.68274e-12
Predicted improvement: 13036379649.916311264
lambda =          1; f = 91974568660675.0312500
lambda =    0.33333; f = 10219395836560.9785156
lambda =    0.11111; f = 1135488198815.8403320
lambda =   0.037037; f = 126165279229.6322632
lambda =   0.012346; f =  14018338589.2858067
lambda =  0.0041152; f =   1557584215.2876763
lambda =  0.0013717; f =    173061553.9735820
lambda = 0.00045725; f =     19227569.0271914
lambda = 0.00015242; f =      2135526.0372841
lambda = 5.0805e-05; f =       236617.3557768
lambda = 1.6935e-05; f =        25696.5290517
lambda =  5.645e-06; f =         2283.8905611
lambda = 1.8817e-06; f =         -309.8440745
lambda = 6.2723e-07; f =         -595.6336052
lambda = 2.0908e-07; f =         -626.8567785
lambda = 6.9692e-08; f =         -630.1596084
lambda = 2.3231e-08; f =         -630.4722341
lambda = 7.7435e-09; f =         -630.4991710
lambda = 2.5812e-09; f =         -630.5009704

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     15962498.1819675
lambda = -2.0908e-07; f =      1767406.1363920
lambda = -6.9692e-08; f =       193942.5994975
lambda = -2.3231e-08; f =        20369.6124690
lambda = -7.7435e-09; f =         1502.4714792
lambda = -2.5812e-09; f =         -454.2970376
Norm of dx  6.375e+09
Predicted improvement:   334542.980405157
lambda =          1; f =        59861.7983726
lambda =    0.33333; f =         6074.1030420
lambda =    0.11111; f =          109.3144607
lambda =   0.037037; f =         -549.5890633
lambda =   0.012346; f =         -621.8693538
lambda =  0.0041152; f =         -629.6483286
lambda =  0.0013717; f =         -630.4286029
lambda = 0.00045725; f =         -630.4953248
lambda = 0.00015242; f =         -630.5008460
lambda = 5.0805e-05; f =         -604.2223626
lambda = 1.6935e-05; f =         -631.2612322
lambda =  5.645e-06; f =         -632.8391141
Norm of dx     817.98
Gradient step!!
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  6.419769e-26.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 175)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',175,0)">line 175</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Correct for low angle: 9.01682e-12
Predicted improvement: 12452616521.132526398
lambda =          1; f = 83921839353306.9531250
lambda =    0.33333; f = 9324648171881.5722656
lambda =    0.11111; f = 1036071803675.6621094
lambda =   0.037037; f = 115119017118.4198761
lambda =   0.012346; f =  12790977470.9755135
lambda =  0.0041152; f =   1421211203.8610766
lambda =  0.0013717; f =    157909145.8144613
lambda = 0.00045725; f =     17544017.6588328
lambda = 0.00015242; f =      1948481.2858500
lambda = 5.0805e-05; f =       215840.1038192
lambda = 1.6935e-05; f =        23389.7779716
lambda =  5.645e-06; f =         2028.1954478
lambda = 1.8817e-06; f =         -338.0513832
lambda = 6.2723e-07; f =         -598.7168763
lambda = 2.0908e-07; f =         -627.1848885
lambda = 6.9692e-08; f =         -630.1913924
lambda = 2.3231e-08; f =         -630.4746728
lambda = 7.7435e-09; f =         -630.4993085
lambda = 2.5812e-09; f =         -630.5009702

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     14563776.8991034
lambda = -2.0908e-07; f =      1612245.7810318
lambda = -6.9692e-08; f =       176786.9341018
lambda = -2.3231e-08; f =        18491.5514495
lambda = -7.7435e-09; f =         1303.1729098
lambda = -2.5812e-09; f =         -473.3162135
Norm of dx 6.0895e+09
Predicted improvement:        0.587026021
lambda =          1; f =         -633.4923771
Norm of dx  0.0052128
Done for param e_a =   0.0692; f = -633.4924
Predicted improvement:        1.761507507
lambda =          1; f =         -635.5399984
Norm of dx   0.028364
Done for param e_v =   0.2503; f = -635.5400
Predicted improvement:        0.168162778
lambda =          1; f =         -635.7210081
Norm of dx  0.0020927
Done for param e_g =   0.0473; f = -635.7210
Predicted improvement:        0.063120319
lambda =          1; f =         -635.7868971
Norm of dx  0.0011367
Done for param e_rer =   0.0399; f = -635.7869
Predicted improvement:        0.670609576
lambda =          1; f =         -636.4262109
Norm of dx  0.0084285
Done for param alp =   0.3576; f = -636.4262
Predicted improvement:        0.019347089
lambda =          1; f =         -636.4453839
Norm of dx 0.00077865
Done for param bet =   0.9203; f = -636.4454
Predicted improvement:        0.016669825
lambda =          1; f =         -636.4620540
Norm of dx 0.00018203
Done for param delt =   0.0997; f = -636.4621
Predicted improvement:        0.104160422
lambda =          1; f =         -636.5658317
Norm of dx   0.031203
Done for param sig =   2.1882; f = -636.5658
Predicted improvement:        0.027150872
lambda =          1; f =         -636.5928007
Norm of dx   0.017205
Done for param phi1 =   1.3417; f = -636.5928
Predicted improvement:        0.685081948
lambda =          1; f =         -637.2883434
Norm of dx    0.31479
Done for param phi2 =   3.3994; f = -637.2883
Predicted improvement:        0.862550646
lambda =          1; f =         -638.0518693
Norm of dx   0.034207
Done for param hf =   0.5114; f = -638.0519
Predicted improvement:        0.019868185
lambda =          1; f =         -638.0717038
Norm of dx    0.01638
Done for param rhoa =   0.4195; f = -638.0717
Predicted improvement:        0.020885949
lambda =          1; f =         -638.0923871
Norm of dx   0.015404
Done for param rhov =   0.2621; f = -638.0924
Predicted improvement:        0.002015664
lambda =          1; f =         -638.0944045
Norm of dx   0.005307
Done for param rhog =   0.5707; f = -638.0944
Predicted improvement:        0.069333818
lambda =          1; f =         -638.1637852
Norm of dx     0.0327
Done for param rhorer =   0.5933; f = -638.1638
Sequence of univariate steps!!
Actual dxnorm 0.3227
FVAL          -638.1638
Improvement   7.6628
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.491189e-21.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.259 s.
 
Iteration 5
Correct for low angle: 8.24774e-12
Predicted improvement: 13827905669.636604309
lambda =          1; f = 663819190229644.1250000
lambda =    0.33333; f = 73757686086139.1093750
lambda =    0.11111; f = 8195297881255.0800781
lambda =   0.037037; f = 910588462177.1767578
lambda =   0.012346; f = 101176431656.7760468
lambda =  0.0041152; f =  11241803983.6705589
lambda =  0.0013717; f =   1249081702.6421361
lambda = 0.00045725; f =    138783935.9010521
lambda = 0.00015242; f =     15419087.0171788
lambda = 5.0805e-05; f =      1712404.7910737
lambda = 1.6935e-05; f =       189614.2373571
lambda =  5.645e-06; f =        20473.0052916
lambda = 1.8817e-06; f =         1698.7649298
lambda = 6.2723e-07; f =         -380.8819119
lambda = 2.0908e-07; f =         -610.2733829
lambda = 6.9692e-08; f =         -635.2825193
lambda = 2.3231e-08; f =         -637.9017234
lambda = 7.7435e-09; f =         -638.1419447
lambda = 2.5812e-09; f =         -638.1625354

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     27314714.2100306
lambda = -2.0908e-07; f =      3027016.2268380
lambda = -6.9692e-08; f =       333312.3298884
lambda = -2.3231e-08; f =        35654.9565733
lambda = -7.7435e-09; f =         3129.5764863
lambda = -2.5812e-09; f =         -301.8033325
Norm of dx 8.3377e+09
Predicted improvement:   220050.093634214
lambda =          1; f =       167345.4041812
lambda =    0.33333; f =        18000.4305951
lambda =    0.11111; f =         1424.6144416
lambda =   0.037037; f =         -411.1670176
lambda =   0.012346; f =         -613.5950660
lambda =  0.0041152; f =         -635.6371543
lambda =  0.0013717; f =         -637.9363137
lambda = 0.00045725; f =         -638.1448498
lambda = 0.00015242; f =         -638.1627631
lambda = 5.0805e-05; f =         -610.7320653
lambda = 1.6935e-05; f =         -637.8506985
lambda =  5.645e-06; f =         -639.6528725
Norm of dx      663.4
Gradient step!!
Predicted improvement:       16.559703259
lambda =          1; f =         -638.0882878
lambda =    0.33333; f =         -638.1609533
lambda =    0.11111; f =         -638.1635922
lambda =   0.037037; f =         -638.1637846
lambda =   0.012346; f =         -636.8044682
lambda =  0.0041152; f =         -639.2767252
lambda =  0.0013717; f =         -639.5911870
lambda = 0.00045725; f =         -639.6393879
lambda = 0.00015242; f =         -639.6491640
lambda = 5.0805e-05; f =         -639.6517237
lambda = 1.6935e-05; f =         -639.6524993
lambda =  5.645e-06; f =         -639.6527492
lambda = 1.8817e-06; f =         -639.6528315
lambda = 6.2723e-07; f =         -639.6528589
lambda = 2.0908e-07; f =         -639.6528680
lambda = 6.9692e-08; f =         -639.6528710
lambda = 2.3231e-08; f =         -639.6528720
lambda = 7.7435e-09; f =         -639.6528724
lambda = 2.5812e-09; f =         -639.6528725

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =         -639.6528862
Norm of dx     5.5344
Predicted improvement:        0.444239866
lambda =          1; f =         -640.1428922
Norm of dx  0.0050868
Done for param e_a =   0.0756; f = -640.1429
Predicted improvement:        1.198138171
lambda =          1; f =         -641.5213035
Norm of dx   0.027401
Done for param e_v =   0.2783; f = -641.5213
Predicted improvement:        0.028157766
lambda =          1; f =         -641.5503932
Norm of dx 0.00095972
Done for param e_g =   0.0493; f = -641.5504
Predicted improvement:        0.040265566
lambda =          1; f =         -641.5925175
Norm of dx 0.00099212
Done for param e_rer =   0.0432; f = -641.5925
Predicted improvement:        0.055711796
lambda =          1; f =         -641.6477647
Norm of dx  0.0023823
Done for param alp =   0.3588; f = -641.6478
Predicted improvement:        0.043667397
lambda =          1; f =         -641.6909718
Norm of dx  0.0012123
Done for param bet =   0.9196; f = -641.6910
Predicted improvement:        0.057328414
lambda =          1; f =         -641.7483021
Norm of dx 0.00033758
Done for param delt =   0.0997; f = -641.7483
Predicted improvement:        0.011195565
lambda =          1; f =         -641.7594446
Norm of dx    0.01006
Done for param sig =   2.1780; f = -641.7594
Predicted improvement:        0.003517797
lambda =          1; f =         -641.7629785
Norm of dx  0.0060687
Done for param phi1 =   1.3479; f = -641.7630
Predicted improvement:        0.689925387
lambda =          1; f =         -642.4629818
Norm of dx    0.33624
Done for param phi2 =   3.7356; f = -642.4630
Predicted improvement:        0.840140867
lambda =          1; f =         -643.2051350
Norm of dx   0.032324
Done for param hf =   0.5437; f = -643.2051
Predicted improvement:        0.001355087
lambda =          1; f =         -643.2064893
Norm of dx  0.0042701
Done for param rhoa =   0.4153; f = -643.2065
Predicted improvement:        0.009357896
lambda =          1; f =         -643.2157744
Norm of dx   0.010545
Done for param rhov =   0.2726; f = -643.2158
Predicted improvement:        0.000227226
lambda =          1; f =         -643.2160016
Norm of dx  0.0018252
Done for param rhog =   0.5725; f = -643.2160
Predicted improvement:        0.019767898
lambda =          1; f =         -643.2357779
Norm of dx   0.018154
Done for param rhorer =   0.5752; f = -643.2358
Sequence of univariate steps!!
Actual dxnorm 0.33991
FVAL          -643.2358
Improvement   5.072
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  8.810984e-21.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.33303 s.
 
Iteration 6
Correct for low angle: 9.58544e-12
Predicted improvement: 11720727026.480577469
lambda =          1; f = 961279298456622.5000000
lambda =    0.33333; f = 106808808884059.0781250
lambda =    0.11111; f = 11867644745995.5136719
lambda =   0.037037; f = 1318626965099.2473145
lambda =   0.012346; f = 146514030555.0363464
lambda =  0.0041152; f =  16279310789.6099300
lambda =  0.0013717; f =   1808803284.1907542
lambda = 0.00045725; f =    200974754.5758004
lambda = 0.00015242; f =     22329019.3920869
lambda = 5.0805e-05; f =      2480119.6504897
lambda = 1.6935e-05; f =       274894.7990409
lambda =  5.645e-06; f =        29938.6217764
lambda = 1.8817e-06; f =         2744.1710975
lambda = 6.2723e-07; f =         -269.8060451
lambda = 2.0908e-07; f =         -602.5906075
lambda = 6.9692e-08; f =         -638.9873159
lambda = 2.3231e-08; f =         -642.8382765
lambda = 7.7435e-09; f =         -643.2025532
lambda = 2.5812e-09; f =         -643.2335412

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     28213908.2243835
lambda = -2.0908e-07; f =      3126801.5714686
lambda = -6.9692e-08; f =       344354.8965932
lambda = -2.3231e-08; f =        36864.0019290
lambda = -7.7435e-09; f =         3254.9401989
lambda = -2.5812e-09; f =         -293.8710965
Norm of dx 8.4738e+09
Predicted improvement:   153058.806446708
lambda =          1; f =       163167.7073180
lambda =    0.33333; f =        17532.3636877
lambda =    0.11111; f =         1368.3190478
lambda =   0.037037; f =         -421.8706932
lambda =   0.012346; f =         -619.2877669
lambda =  0.0041152; f =         -640.7762516
lambda =  0.0013717; f =         -643.0149458
lambda = 0.00045725; f =         -643.2173042
lambda = 0.00015242; f =         -643.2347617
lambda = 5.0805e-05; f =         -622.4879313
lambda = 1.6935e-05; f =         -643.1779394
lambda =  5.645e-06; f =         -644.3173283
Norm of dx     553.28
Gradient step!!
Predicted improvement:       16.588185355
lambda =          1; f =         -643.1187064
lambda =    0.33333; f =         -643.2326977
lambda =    0.11111; f =         -643.2355636
lambda =   0.037037; f =         -643.2357769
lambda =   0.012346; f =         -641.1671156
lambda =  0.0041152; f =         -643.9013423
lambda =  0.0013717; f =         -644.2491160
lambda = 0.00045725; f =         -644.3024185
lambda = 0.00015242; f =         -644.3132281
lambda = 5.0805e-05; f =         -644.3160582
lambda = 1.6935e-05; f =         -644.3169156
lambda =  5.645e-06; f =         -644.3171919
lambda = 1.8817e-06; f =         -644.3172829
lambda = 6.2723e-07; f =         -644.3173132
lambda = 2.0908e-07; f =         -644.3173232
lambda = 6.9692e-08; f =         -644.3173266
lambda = 2.3231e-08; f =         -644.3173277
lambda = 7.7435e-09; f =         -644.3173281
lambda = 2.5812e-09; f =         -644.3173282

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =         -644.3173433
Norm of dx     6.5463
Predicted improvement:        0.429741013
lambda =          1; f =         -644.7915612
Norm of dx  0.0054535
Done for param e_a =   0.0823; f = -644.7916
Predicted improvement:        0.759896083
lambda =          1; f =         -645.6479750
Norm of dx   0.025271
Done for param e_v =   0.3039; f = -645.6480
Predicted improvement:        0.003510122
lambda =          1; f =         -645.6515326
Norm of dx 0.00035672
Done for param e_g =   0.0502; f = -645.6515
Predicted improvement:        0.022744701
lambda =          1; f =         -645.6749664
Norm of dx 0.00080187
Done for param e_rer =   0.0456; f = -645.6750
Predicted improvement:        0.000390445
lambda =          1; f =         -645.6753552
Norm of dx 2.3762e-05
Done for param e_yw =   0.0098; f = -645.6754
Predicted improvement:        0.000107532
lambda =          1; f =         -645.6754627
Norm of dx 0.00010502
Done for param alp =   0.3575; f = -645.6755
Predicted improvement:        0.039967621
lambda =          1; f =         -645.7146095
Norm of dx  0.0012006
Done for param bet =   0.9189; f = -645.7146
Predicted improvement:        0.057350831
lambda =          1; f =         -645.7719622
Norm of dx 0.00033764
Done for param delt =   0.0998; f = -645.7720
Predicted improvement:        0.000799487
lambda =          1; f =         -645.7727685
Norm of dx  0.0026215
Done for param sig =   2.1753; f = -645.7728
Predicted improvement:        0.010682436
lambda =          1; f =         -645.7834695
Norm of dx   0.010448
Done for param phi1 =   1.3584; f = -645.7835
Predicted improvement:        0.547055577
lambda =          1; f =         -646.3372551
Norm of dx    0.31662
Done for param phi2 =   4.0522; f = -646.3373
Predicted improvement:        0.742625308
lambda =          1; f =         -646.9974860
Norm of dx   0.028692
Done for param hf =   0.5723; f = -646.9975
Predicted improvement:        0.000202542
lambda =          1; f =         -646.9976885
Norm of dx  0.0016565
Done for param rhoa =   0.4136; f = -646.9977
Predicted improvement:        0.003399775
lambda =          1; f =         -647.0010706
Norm of dx  0.0064985
Done for param rhov =   0.2791; f = -647.0011
Predicted improvement:        0.001005188
lambda =          1; f =         -647.0020752
Norm of dx  0.0038815
Done for param rhog =   0.5764; f = -647.0021
Predicted improvement:        0.008502010
lambda =          1; f =         -647.0105798
Norm of dx   0.012204
Done for param rhorer =   0.5630; f = -647.0106
Sequence of univariate steps!!
Actual dxnorm 0.31954
FVAL          -647.0106
Improvement   3.7748
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.943009e-21.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.34802 s.
 
Iteration 7
Correct for low angle: 1.13417e-11
Predicted improvement: 9814871289.287574768
lambda =          1; f = 1051831237832435.1250000
lambda =    0.33333; f = 116870135370765.9062500
lambda =    0.11111; f = 12985569874314.9121094
lambda =   0.037037; f = 1442840855954.0776367
lambda =   0.012346; f = 160315569883.7275696
lambda =  0.0041152; f =  17812813791.0676689
lambda =  0.0013717; f =   1979192048.7772696
lambda = 0.00045725; f =    219906685.2652369
lambda = 0.00015242; f =     24432514.1595335
lambda = 5.0805e-05; f =      2713821.9168661
lambda = 1.6935e-05; f =       300853.3258365
lambda =  5.645e-06; f =        32817.8867990
lambda = 1.8817e-06; f =         3060.1966594
lambda = 6.2723e-07; f =         -238.2103243
lambda = 2.0908e-07; f =         -602.4669242
lambda = 6.9692e-08; f =         -642.3396709
lambda = 2.3231e-08; f =         -646.5699727
lambda = 7.7435e-09; f =         -646.9737333
lambda = 2.5812e-09; f =         -647.0079786

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     27138334.5904475
lambda = -2.0908e-07; f =      3007434.6284216
lambda = -6.9692e-08; f =       331136.7566718
lambda = -2.3231e-08; f =        35408.0246564
lambda = -7.7435e-09; f =         3095.1634024
lambda = -2.5812e-09; f =         -313.1948756
Norm of dx 8.3108e+09
Predicted improvement:   111580.175926564
lambda =          1; f =       135185.9393557
lambda =    0.33333; f =        14422.2452167
lambda =    0.11111; f =         1020.1850851
lambda =   0.037037; f =         -463.6698588
lambda =   0.012346; f =         -627.2219476
lambda =  0.0041152; f =         -644.9916167
lambda =  0.0013717; f =         -646.8317626
lambda = 0.00045725; f =         -646.9955888
lambda = 0.00015242; f =         -647.0098012
lambda = 5.0805e-05; f =         -632.1478349
lambda = 1.6935e-05; f =         -647.1667160
lambda =  5.645e-06; f =         -647.8324693
Norm of dx      472.4
Predicted improvement:       15.974247913
lambda =          1; f =         -646.8341554
lambda =    0.33333; f =         -647.0062733
lambda =    0.11111; f =         -647.0102971
lambda =   0.037037; f =         -647.0105769
lambda =   0.012346; f =         -643.9564904
lambda =  0.0041152; f =         -647.3380344
lambda =  0.0013717; f =         -647.7562699
lambda = 0.00045725; f =         -647.8169151
lambda = 0.00015242; f =         -647.8283785
lambda = 5.0805e-05; f =         -647.8312272
lambda = 1.6935e-05; f =         -647.8320688
lambda =  5.645e-06; f =         -647.8323373
lambda = 1.8817e-06; f =         -647.8324254
lambda = 6.2723e-07; f =         -647.8324547
lambda = 2.0908e-07; f =         -647.8324644
lambda = 6.9692e-08; f =         -647.8324676
lambda = 2.3231e-08; f =         -647.8324687
lambda = 7.7435e-09; f =         -647.8324691
lambda = 2.5812e-09; f =         -647.8324692

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =         -647.8324838
Norm of dx     8.3695
Predicted improvement:        0.402029569
lambda =          1; f =         -648.2742755
Norm of dx  0.0057498
Done for param e_a =   0.0891; f = -648.2743
Predicted improvement:        0.436139765
lambda =          1; f =         -648.7564764
Norm of dx   0.021681
Done for param e_v =   0.3259; f = -648.7565
Predicted improvement:        0.000444301
lambda =          1; f =         -648.7569226
Norm of dx 0.00012989
Done for param e_g =   0.0508; f = -648.7569
Predicted improvement:        0.014941773
lambda =          1; f =         -648.7722075
Norm of dx 0.00068342
Done for param e_rer =   0.0475; f = -648.7722
Predicted improvement:        0.015207396
lambda =          1; f =         -648.7876248
Norm of dx  0.0012532
Done for param alp =   0.3551; f = -648.7876
Predicted improvement:        0.030999480
lambda =          1; f =         -648.8180177
Norm of dx  0.0010865
Done for param bet =   0.9182; f = -648.8180
Predicted improvement:        0.044164095
lambda =          1; f =         -648.8621830
Norm of dx 0.00029628
Done for param delt =   0.0998; f = -648.8622
Predicted improvement:        0.000247981
lambda =          1; f =         -648.8624294
Norm of dx   0.001444
Done for param sig =   2.1738; f = -648.8624
Predicted improvement:        0.008841622
lambda =          1; f =         -648.8713254
Norm of dx  0.0093668
Done for param phi1 =   1.3678; f = -648.8713
Predicted improvement:        0.377039979
lambda =          1; f =         -649.2520007
Norm of dx    0.27516
Done for param phi2 =   4.3274; f = -649.2520
Predicted improvement:        0.656540537
lambda =          1; f =         -649.8396295
Norm of dx   0.025424
Done for param hf =   0.5977; f = -649.8396
Predicted improvement:        0.000067706
lambda =          1; f =         -649.8396972
Norm of dx 0.00096473
Done for param rhoa =   0.4126; f = -649.8397
Predicted improvement:        0.000160809
lambda =          1; f =         -649.8398578
Norm of dx  0.0014392
Done for param rhov =   0.2806; f = -649.8399
Predicted improvement:        0.001150213
lambda =          1; f =         -649.8410073
Norm of dx  0.0041761
Done for param rhog =   0.5806; f = -649.8410
Predicted improvement:        0.004850369
lambda =          1; f =         -649.8458589
Norm of dx  0.0093731
Done for param rhorer =   0.5536; f = -649.8459
Sequence of univariate steps!!
Actual dxnorm 0.27765
FVAL          -649.8459
Improvement   2.8353
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.121451e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.32075 s.
 
Iteration 8
Correct for low angle: 1.4338e-11
Predicted improvement: 7598099684.171936035
lambda =          1; f = 918574478420355.1250000
lambda =    0.33333; f = 102063828879044.6875000
lambda =    0.11111; f = 11340424745107.3300781
lambda =   0.037037; f = 1260046964887.3730469
lambda =   0.012346; f = 140005141600.9459839
lambda =  0.0041152; f =  15556100888.9830437
lambda =  0.0013717; f =   1728446620.2005134
lambda = 0.00045725; f =    192046230.8143125
lambda = 0.00015242; f =     21336956.5908098
lambda = 5.0805e-05; f =      2369886.1362479
lambda = 1.6935e-05; f =       262641.6894043
lambda =  5.645e-06; f =        28571.6189124
lambda = 1.8817e-06; f =         2586.5478298
lambda = 6.2723e-07; f =         -293.1282718
lambda = 2.0908e-07; f =         -611.0192460
lambda = 6.9692e-08; f =         -645.7872516
lambda = 2.3231e-08; f =         -649.4660762
lambda = 7.7435e-09; f =         -649.8140737
lambda = 2.5812e-09; f =         -649.8436568

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     22376382.2987964
lambda = -2.0908e-07; f =      2479003.6760432
lambda = -6.9692e-08; f =       272645.4743624
lambda = -2.3231e-08; f =        28981.7274078
lambda = -7.7435e-09; f =         2403.6956500
lambda = -2.5812e-09; f =         -384.1834938
Norm of dx  7.547e+09
Predicted improvement:       14.877939442
lambda =          1; f =         -649.6216151
lambda =    0.33333; f =         -649.8398743
lambda =    0.11111; f =         -649.8455336
lambda =   0.037037; f =         -649.8458552
lambda =   0.012346; f =         -646.0319225
lambda =  0.0041152; f =         -649.5037967
lambda =  0.0013717; f =         -649.8350660
lambda = 0.00045725; f =         -649.8537303
Norm of dx     10.225
Predicted improvement:        0.526468273
lambda =          1; f =         -650.4394355
Norm of dx  0.0069066
Done for param e_a =   0.0960; f = -650.4394
Predicted improvement:        0.333090783
lambda =          1; f =         -650.8034395
Norm of dx   0.020652
Done for param e_v =   0.3468; f = -650.8034
Predicted improvement:        0.028775992
lambda =          1; f =         -650.8331413
Norm of dx  0.0010199
Done for param e_g =   0.0518; f = -650.8331
Predicted improvement:        0.212082795
lambda =          1; f =         -651.0618718
Norm of dx  0.0024547
Done for param e_rer =   0.0499; f = -651.0619
Predicted improvement:        0.133518335
lambda =          1; f =         -651.1987427
Norm of dx  0.0036797
Done for param alp =   0.3511; f = -651.1987
Predicted improvement:        0.011646319
lambda =          1; f =         -651.2102567
Norm of dx 0.00067544
Done for param bet =   0.9191; f = -651.2103
Predicted improvement:        0.006776498
lambda =          1; f =         -651.2170332
Norm of dx 0.00011607
Done for param delt =   0.0998; f = -651.2170
Predicted improvement:        0.000062114
lambda =          1; f =         -651.2170953
Norm of dx 0.00071039
Done for param sig =   2.1755; f = -651.2171
Predicted improvement:        0.003590791
lambda =          1; f =         -651.2206992
Norm of dx   0.005918
Done for param phi1 =   1.3764; f = -651.2207
Predicted improvement:        0.222904012
lambda =          1; f =         -651.4451753
Norm of dx    0.21907
Done for param phi2 =   4.5494; f = -651.4452
Predicted improvement:        0.602004543
lambda =          1; f =         -651.9862091
Norm of dx   0.023087
Done for param hf =   0.6207; f = -651.9862
Predicted improvement:        0.000030568
lambda =          1; f =         -651.9862397
Norm of dx  0.0006522
Done for param rhoa =   0.4133; f = -651.9862
Predicted improvement:        0.000288489
lambda =          1; f =         -651.9865281
Norm of dx    0.00211
Done for param rhog =   0.5829; f = -651.9865
Predicted improvement:        0.006483295
lambda =          1; f =         -651.9930134
Norm of dx    0.01106
Done for param rhorer =   0.5424; f = -651.9930
Sequence of univariate steps!!
Actual dxnorm 0.22482
FVAL          -651.993
Improvement   2.1472
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.787138e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.3243 s.
 
Iteration 9
Correct for low angle: 1.89573e-11
Predicted improvement: 5678282309.477713585
lambda =          1; f = 788450718311466.0000000
lambda =    0.33333; f = 87605633425510.9218750
lambda =    0.11111; f = 9733958621643.1445312
lambda =   0.037037; f = 1081550741626.1176758
lambda =   0.012346; f = 120172232131.3358917
lambda =  0.0041152; f =  13352445689.2265568
lambda =  0.0013717; f =   1483596511.0522454
lambda = 0.00045725; f =    164840818.6084516
lambda = 0.00015242; f =     18314184.1213696
lambda = 5.0805e-05; f =      2034038.8841842
lambda = 1.6935e-05; f =       225329.6286481
lambda =  5.645e-06; f =        24426.0063908
lambda = 1.8817e-06; f =         2124.7267102
lambda = 6.2723e-07; f =         -346.1078176
lambda = 2.0908e-07; f =         -618.7305642
lambda = 6.9692e-08; f =         -648.5252768
lambda = 2.3231e-08; f =         -651.6704410
lambda = 7.7435e-09; f =         -651.9659259
lambda = 2.5812e-09; f =         -651.9912600

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     17727850.2770700
lambda = -2.0908e-07; f =      1963233.3470442
lambda = -6.9692e-08; f =       215580.7755546
lambda = -2.3231e-08; f =        22720.9690801
lambda = -7.7435e-09; f =         1733.3715555
lambda = -2.5812e-09; f =         -451.4984695
Norm of dx 6.7181e+09
Predicted improvement:       11.630527574
lambda =          1; f =         -651.8023757
lambda =    0.33333; f =         -651.9874485
lambda =    0.11111; f =         -651.9926473
lambda =   0.037037; f =         -651.9930082
lambda =   0.012346; f =         -647.5622703
lambda =  0.0041152; f =         -651.5645866
lambda =  0.0013717; f =         -651.9666845
lambda = 0.00045725; f =         -651.9971787
Norm of dx     13.204
Predicted improvement:        0.457607975
lambda =          1; f =         -652.5026029
Norm of dx  0.0070123
Done for param e_a =   0.1030; f = -652.5026
Predicted improvement:        0.153220028
lambda =          1; f =         -652.6657849
Norm of dx   0.015439
Done for param e_v =   0.3625; f = -652.6658
Predicted improvement:        0.007680558
lambda =          1; f =         -652.6735979
Norm of dx 0.00054564
Done for param e_g =   0.0523; f = -652.6736
Predicted improvement:        0.130916806
lambda =          1; f =         -652.8125476
Norm of dx  0.0020691
Done for param e_rer =   0.0520; f = -652.8125
Predicted improvement:        0.132682736
lambda =          1; f =         -652.9489246
Norm of dx  0.0036974
Done for param alp =   0.3472; f = -652.9489
Predicted improvement:        0.004132807
lambda =          1; f =         -652.9530466
Norm of dx 0.00040826
Done for param bet =   0.9197; f = -652.9530
Predicted improvement:        0.007491066
lambda =          1; f =         -652.9605378
Norm of dx 0.00012203
Done for param delt =   0.0998; f = -652.9605
Predicted improvement:        0.002190903
lambda =          1; f =         -652.9627235
Norm of dx  0.0041581
Done for param sig =   2.1740; f = -652.9627
Predicted improvement:        0.000682681
lambda =          1; f =         -652.9634052
Norm of dx  0.0025622
Done for param phi1 =   1.3823; f = -652.9634
Predicted improvement:        0.141746684
lambda =          1; f =         -653.1059212
Norm of dx    0.17943
Done for param phi2 =   4.7331; f = -653.1059
Predicted improvement:        0.528340556
lambda =          1; f =         -653.5838931
Norm of dx   0.020461
Done for param hf =   0.6411; f = -653.5839
Predicted improvement:        0.003278988
lambda =          1; f =         -653.5871897
Norm of dx  0.0067191
Done for param rhov =   0.2737; f = -653.5872
Predicted improvement:        0.000414389
lambda =          1; f =         -653.5876040
Norm of dx  0.0025373
Done for param rhog =   0.5856; f = -653.5876
Predicted improvement:        0.003983948
lambda =          1; f =         -653.5915889
Norm of dx  0.0088051
Done for param rhorer =   0.5336; f = -653.5916
Sequence of univariate steps!!
Actual dxnorm 0.18611
FVAL          -653.5916
Improvement   1.5986
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.207831e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31454 s.
 
Iteration 10
Correct for low angle: 2.51945e-11
Predicted improvement: 4116079664.589533329
lambda =          1; f = 631243384323512.0000000
lambda =    0.33333; f = 70138152060093.4921875
lambda =    0.11111; f = 7793127421751.7470703
lambda =   0.037037; f = 865902851504.1793213
lambda =   0.012346; f =  96211362442.7104340
lambda =  0.0041152; f =  10690129165.1066513
lambda =  0.0013717; f =   1187784340.3001301
lambda = 0.00045725; f =    131973058.0751475
lambda = 0.00015242; f =     14662296.5234612
lambda = 5.0805e-05; f =      1628301.8078679
lambda = 1.6935e-05; f =       180256.0996087
lambda =  5.645e-06; f =        19419.6838004
lambda = 1.8817e-06; f =         1568.1502881
lambda = 6.2723e-07; f =         -409.0372354
lambda = 2.0908e-07; f =         -627.0449122
lambda = 6.9692e-08; f =         -650.8377861
lambda = 2.3231e-08; f =         -653.3382558
lambda = 7.7435e-09; f =         -653.5702973
lambda = 2.5812e-09; f =         -653.5903396

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     13466128.7035360
lambda = -2.0908e-07; f =      1490471.9507644
lambda = -6.9692e-08; f =       163305.1711283
lambda = -2.3231e-08; f =        16996.1019307
lambda = -7.7435e-09; f =         1124.1725858
lambda = -2.5812e-09; f =         -511.1697064
Norm of dx 5.8558e+09
Predicted improvement:       10.838510130
lambda =          1; f =         -653.3372705
lambda =    0.33333; f =         -653.5820890
lambda =    0.11111; f =         -653.5909813
lambda =   0.037037; f =         -653.5915721
lambda =   0.012346; f =         -647.2066985
lambda =  0.0041152; f =         -652.9417814
lambda =  0.0013717; f =         -653.5392162
lambda = 0.00045725; f =         -653.5923778
lambda = 0.00015242; f =         -653.5938792
Norm of dx     13.966
Predicted improvement:        0.353922568
lambda =          1; f =         -653.9809043
Norm of dx  0.0067202
Done for param e_a =   0.1098; f = -653.9809
Predicted improvement:        0.063446406
lambda =          1; f =         -654.0472726
Norm of dx    0.01063
Done for param e_v =   0.3732; f = -654.0473
Predicted improvement:        0.003463906
lambda =          1; f =         -654.0507769
Norm of dx 0.00037227
Done for param e_g =   0.0527; f = -654.0508
Predicted improvement:        0.082657040
lambda =          1; f =         -654.1377695
Norm of dx   0.001733
Done for param e_rer =   0.0538; f = -654.1378
Predicted improvement:        0.114006155
lambda =          1; f =         -654.2540333
Norm of dx  0.0034752
Done for param alp =   0.3436; f = -654.2540
Predicted improvement:        0.001288712
lambda =          1; f =         -654.2553285
Norm of dx 0.00023142
Done for param bet =   0.9200; f = -654.2553
Predicted improvement:        0.001801002
lambda =          1; f =         -654.2571295
Norm of dx 5.9834e-05
Done for param delt =   0.0998; f = -654.2571
Predicted improvement:        0.005562627
lambda =          1; f =         -654.2627106
Norm of dx  0.0064938
Done for param sig =   2.1683; f = -654.2627
Predicted improvement:        0.000679701
lambda =          1; f =         -654.2633938
Norm of dx  0.0025215
Done for param phi1 =   1.3860; f = -654.2634
Predicted improvement:        0.091458150
lambda =          1; f =         -654.3552365
Norm of dx    0.14712
Done for param phi2 =   4.8818; f = -654.3552
Predicted improvement:        0.462609433
lambda =          1; f =         -654.7767232
Norm of dx   0.018137
Done for param hf =   0.6593; f = -654.7767
Predicted improvement:        0.000079657
lambda =          1; f =         -654.7768029
Norm of dx  0.0010734
Done for param rhoa =   0.4122; f = -654.7768
Predicted improvement:        0.009442199
lambda =          1; f =         -654.7863240
Norm of dx   0.011485
Done for param rhov =   0.2622; f = -654.7863
Predicted improvement:        0.000413799
lambda =          1; f =         -654.7867376
Norm of dx  0.0025394
Done for param rhog =   0.5882; f = -654.7867
Predicted improvement:        0.002469941
lambda =          1; f =         -654.7892080
Norm of dx  0.0070151
Done for param rhorer =   0.5265; f = -654.7892
Sequence of univariate steps!!
Actual dxnorm 0.15117
FVAL          -654.7892
Improvement   1.1976
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.041689e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.30934 s.
 
Iteration 11
Correct for low angle: 3.27377e-11
Predicted improvement: 3024837043.898072720
lambda =          1; f = 524909872630117.3125000
lambda =    0.33333; f = 58323317561861.4765625
lambda =    0.11111; f = 6480368077848.1279297
lambda =   0.037037; f = 720040717110.4954834
lambda =   0.012346; f =  80004463597.0667572
lambda =  0.0041152; f =   8889364285.0423012
lambda =  0.0013717; f =    987699906.1213853
lambda = 0.00045725; f =    109741638.1574402
lambda = 0.00015242; f =     12192199.7631280
lambda = 5.0805e-05; f =      1353866.6872310
lambda = 1.6935e-05; f =       149769.2172077
lambda =  5.645e-06; f =        16033.5343562
lambda = 1.8817e-06; f =         1191.6370066
lambda = 6.2723e-07; f =         -451.7199415
lambda = 2.0908e-07; f =         -632.7780974
lambda = 6.9692e-08; f =         -652.5151479
lambda = 2.3231e-08; f =         -654.5817017
lambda = 7.7435e-09; f =         -654.7717801
lambda = 2.5812e-09; f =         -654.7882732

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     10846382.2833964
lambda = -2.0908e-07; f =      1199919.8593016
lambda = -6.9692e-08; f =       131197.8394496
lambda = -2.3231e-08; f =        13486.6563510
lambda = -7.7435e-09; f =          752.8695683
lambda = -2.5812e-09; f =         -546.9241177
Norm of dx  5.256e+09
Predicted improvement:        9.711059969
lambda =          1; f =         -654.5535350
lambda =    0.33333; f =         -654.7762895
lambda =    0.11111; f =         -654.7880997
lambda =   0.037037; f =         -654.7891596
lambda =   0.012346; f =         -644.7713476
lambda =  0.0041152; f =         -653.7296438
lambda =  0.0013717; f =         -654.6892472
lambda = 0.00045725; f =         -654.7840220
lambda = 0.00015242; f =         -654.7906053
Norm of dx     11.965
Predicted improvement:        0.256173047
lambda =          1; f =         -655.0686947
Norm of dx  0.0061749
Done for param e_a =   0.1159; f = -655.0687
Predicted improvement:        0.027189582
lambda =          1; f =         -655.0967434
Norm of dx  0.0072774
Done for param e_v =   0.3806; f = -655.0967
Predicted improvement:        0.001810722
lambda =          1; f =         -655.0985696
Norm of dx 0.00027188
Done for param e_g =   0.0530; f = -655.0986
Predicted improvement:        0.054102246
lambda =          1; f =         -655.1550034
Norm of dx  0.0014638
Done for param e_rer =   0.0552; f = -655.1550
Predicted improvement:        0.083603493
lambda =          1; f =         -655.2398296
Norm of dx  0.0030115
Done for param alp =   0.3406; f = -655.2398
Predicted improvement:        0.000195599
lambda =          1; f =         -655.2400241
Norm of dx 9.2184e-05
Done for param bet =   0.9202; f = -655.2400
Predicted improvement:        0.002468782
lambda =          1; f =         -655.2424929
Norm of dx 7.0051e-05
Done for param delt =   0.0999; f = -655.2425
Predicted improvement:        0.010502285
lambda =          1; f =         -655.2529025
Norm of dx  0.0088192
Done for param sig =   2.1600; f = -655.2529
Predicted improvement:        0.000914551
lambda =          1; f =         -655.2538157
Norm of dx   0.002905
Done for param phi1 =   1.3901; f = -655.2538
Predicted improvement:        0.058007555
lambda =          1; f =         -655.3120139
Norm of dx    0.11906
Done for param phi2 =   5.0021; f = -655.3120
Predicted improvement:        0.389701983
lambda =          1; f =         -655.6699198
Norm of dx   0.015798
Done for param hf =   0.6751; f = -655.6699
Predicted improvement:        0.000097231
lambda =          1; f =         -655.6700170
Norm of dx  0.0011963
Done for param rhoa =   0.4110; f = -655.6700
Predicted improvement:        0.013347928
lambda =          1; f =         -655.6834773
Norm of dx   0.013721
Done for param rhov =   0.2484; f = -655.6835
Predicted improvement:        0.000310624
lambda =          1; f =         -655.6837879
Norm of dx  0.0022016
Done for param rhog =   0.5905; f = -655.6838
Predicted improvement:        0.001516617
lambda =          1; f =         -655.6853047
Norm of dx  0.0055501
Done for param rhorer =   0.5210; f = -655.6853
Sequence of univariate steps!!
Actual dxnorm 0.12308
FVAL          -655.6853
Improvement   0.8961
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.526712e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31457 s.
 
Iteration 12
Correct for low angle: 4.27176e-11
Predicted improvement: 2263938832.516389847
lambda =          1; f = 467829662488144.0000000
lambda =    0.33333; f = 51981072059162.5312500
lambda =    0.11111; f = 5775674155980.7626953
lambda =   0.037037; f = 641741400083.6621094
lambda =   0.012346; f =  71304542024.4626617
lambda =  0.0041152; f =   7922707179.5217447
lambda =  0.0013717; f =    880293843.2220668
lambda = 0.00045725; f =     97807725.0496506
lambda = 0.00015242; f =     10866240.5396758
lambda = 5.0805e-05; f =      1206548.0912353
lambda = 1.6935e-05; f =       133403.3698558
lambda =  5.645e-06; f =        14215.5735043
lambda = 1.8817e-06; f =          989.2709095
lambda = 6.2723e-07; f =         -474.9154366
lambda = 2.0908e-07; f =         -636.1058283
lambda = 6.9692e-08; f =         -653.6658993
lambda = 2.3231e-08; f =         -655.5014172
lambda = 7.7435e-09; f =         -655.6698457
lambda = 2.5812e-09; f =         -655.6845240

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      9477309.1930935
lambda = -2.0908e-07; f =      1048103.5770351
lambda = -6.9692e-08; f =       114429.8170454
lambda = -2.3231e-08; f =        11656.4969833
lambda = -7.7435e-09; f =          559.9720278
lambda = -2.5812e-09; f =         -565.4040366
Norm of dx 4.9135e+09
Predicted improvement:        9.404782345
lambda =          1; f =         -655.4407839
lambda =    0.33333; f =         -655.6655405
lambda =    0.11111; f =         -655.6834800
lambda =   0.037037; f =         -655.6852028
lambda =   0.012346; f =         -640.6719887
lambda =  0.0041152; f =         -654.0690937
lambda =  0.0013717; f =         -655.5229359
lambda = 0.00045725; f =         -655.6729978
lambda = 0.00015242; f =         -655.6858485
lambda = 5.0805e-05; f =         -655.6860022
lambda = 9.8216e-05; f =         -655.6861875
Norm of dx     9.1176
Predicted improvement:        0.177635879
lambda =          1; f =         -655.8766502
Norm of dx  0.0055203
Done for param e_a =   0.1215; f = -655.8767
Predicted improvement:        0.013162305
lambda =          1; f =         -655.8901036
Norm of dx  0.0052116
Done for param e_v =   0.3859; f = -655.8901
Predicted improvement:        0.001082765
lambda =          1; f =         -655.8911935
Norm of dx  0.0002117
Done for param e_g =   0.0532; f = -655.8912
Predicted improvement:        0.034612708
lambda =          1; f =         -655.9270277
Norm of dx   0.001213
Done for param e_rer =   0.0564; f = -655.9270
Predicted improvement:        0.053351731
lambda =          1; f =         -655.9813857
Norm of dx  0.0024203
Done for param alp =   0.3381; f = -655.9814
Predicted improvement:        0.001643708
lambda =          1; f =         -655.9830294
Norm of dx 5.7157e-05
Done for param delt =   0.0999; f = -655.9830
Predicted improvement:        0.014739904
lambda =          1; f =         -655.9977831
Norm of dx   0.010215
Done for param sig =   2.1500; f = -655.9978
Predicted improvement:        0.001666007
lambda =          1; f =         -655.9994546
Norm of dx  0.0038742
Done for param phi1 =   1.3947; f = -655.9995
Predicted improvement:        0.037596793
lambda =          1; f =         -656.0371480
Norm of dx   0.097063
Done for param phi2 =   5.0997; f = -656.0371
Predicted improvement:        0.314313930
lambda =          1; f =         -656.3285863
Norm of dx   0.013502
Done for param hf =   0.6886; f = -656.3286
Predicted improvement:        0.000115433
lambda =          1; f =         -656.3287017
Norm of dx  0.0013137
Done for param rhoa =   0.4097; f = -656.3287
Predicted improvement:        0.013334027
lambda =          1; f =         -656.3421225
Norm of dx   0.013743
Done for param rhov =   0.2347; f = -656.3421
Predicted improvement:        0.000211866
lambda =          1; f =         -656.3423343
Norm of dx  0.0018187
Done for param rhog =   0.5924; f = -656.3423
Predicted improvement:        0.000928881
lambda =          1; f =         -656.3432633
Norm of dx   0.004377
Done for param rhorer =   0.5166; f = -656.3433
Sequence of univariate steps!!
Actual dxnorm 0.10053
FVAL          -656.3433
Improvement   0.65796
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.962033e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.32813 s.
 
Iteration 13
Correct for low angle: 5.77729e-11
Predicted improvement: 1623228616.175179482
lambda =          1; f = 394741353788599.1875000
lambda =    0.33333; f = 43860148971769.2734375
lambda =    0.11111; f = 4873349402307.5087891
lambda =   0.037037; f = 541483105391.1694336
lambda =   0.012346; f =  60164735260.0488205
lambda =  0.0041152; f =   6684952124.6003847
lambda =  0.0013717; f =    742765921.1092578
lambda = 0.00045725; f =     82526983.8335124
lambda = 0.00015242; f =      9168426.6550748
lambda = 5.0805e-05; f =      1017917.4057653
lambda = 1.6935e-05; f =       112449.0664636
lambda =  5.645e-06; f =        11888.5008316
lambda = 1.8817e-06; f =          730.6892299
lambda = 6.2723e-07; f =         -504.1013142
lambda = 2.0908e-07; f =         -639.8792937
lambda = 6.9692e-08; f =         -654.6516721
lambda = 2.3231e-08; f =         -656.1900725
lambda = 7.7435e-09; f =         -656.3304025
lambda = 2.5812e-09; f =         -656.3426732

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      7903974.4910200
lambda = -2.0908e-07; f =       873665.6520948
lambda = -6.9692e-08; f =        95173.1175759
lambda = -2.3231e-08; f =         9558.2386440
lambda = -7.7435e-09; f =          340.2333487
lambda = -2.5812e-09; f =         -585.7425970
Norm of dx 4.4876e+09
Predicted improvement:        3.455053065
lambda =          1; f =         -632.0718435
lambda =    0.33333; f =         -656.2652639
lambda =    0.11111; f =         -656.3431906
lambda =   0.037037; f =         -643.4957562
lambda =   0.012346; f =         -654.9726313
lambda =  0.0041152; f =         -656.2099266
lambda =  0.0013717; f =         -656.3347672
lambda = 0.00045725; f =         -656.3444257
Norm of dx     7.7431
Predicted improvement:        0.116574561
lambda =          1; f =         -656.4678451
Norm of dx  0.0047565
Done for param e_a =   0.1262; f = -656.4678
Predicted improvement:        0.007766321
lambda =          1; f =         -656.4757450
Norm of dx  0.0040761
Done for param e_v =   0.3898; f = -656.4757
Predicted improvement:        0.000755452
lambda =          1; f =         -656.4765047
Norm of dx  0.0001777
Done for param e_g =   0.0534; f = -656.4765
Predicted improvement:        0.021908163
lambda =          1; f =         -656.4990347
Norm of dx 0.00099339
Done for param e_rer =   0.0574; f = -656.4990
Predicted improvement:        0.031326215
lambda =          1; f =         -656.5306926
Norm of dx  0.0018752
Done for param alp =   0.3363; f = -656.5307
Predicted improvement:        0.000107995
lambda =          1; f =         -656.5308008
Norm of dx  7.014e-05
Done for param bet =   0.9201; f = -656.5308
Predicted improvement:        0.002644508
lambda =          1; f =         -656.5334454
Norm of dx 7.2495e-05
Done for param delt =   0.0999; f = -656.5334
Predicted improvement:        0.014822637
lambda =          1; f =         -656.5482502
Norm of dx   0.010079
Done for param sig =   2.1384; f = -656.5483
Predicted improvement:        0.003174871
lambda =          1; f =         -656.5514379
Norm of dx  0.0052996
Done for param phi1 =   1.3994; f = -656.5514
Predicted improvement:        0.025921332
lambda =          1; f =         -656.5774143
Norm of dx   0.081385
Done for param phi2 =   5.1779; f = -656.5774
Predicted improvement:        0.243280990
lambda =          1; f =         -656.8052615
Norm of dx    0.01135
Done for param hf =   0.7001; f = -656.8053
Predicted improvement:        0.000069478
lambda =          1; f =         -656.8053309
Norm of dx  0.0010261
Done for param rhoa =   0.4086; f = -656.8053
Predicted improvement:        0.010886260
lambda =          1; f =         -656.8162604
Norm of dx   0.012405
Done for param rhov =   0.2222; f = -656.8163
Predicted improvement:        0.000118332
lambda =          1; f =         -656.8163787
Norm of dx  0.0013594
Done for param rhog =   0.5938; f = -656.8164
Predicted improvement:        0.000541160
lambda =          1; f =         -656.8169199
Norm of dx  0.0033624
Done for param rhorer =   0.5132; f = -656.8169
Sequence of univariate steps!!
Actual dxnorm 0.08134
FVAL          -656.8169
Improvement   0.47366
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  5.252506e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31837 s.
 
Iteration 14
Correct for low angle: 7.99059e-11
Predicted improvement: 1139468982.581782818
lambda =          1; f = 332832899796850.3750000
lambda =    0.33333; f = 36981431955882.0859375
lambda =    0.11111; f = 4109047543088.7304688
lambda =   0.037037; f = 456560687067.3359985
lambda =   0.012346; f =  50728914494.5621185
lambda =  0.0041152; f =   5636528759.3068199
lambda =  0.0013717; f =    626274824.1109135
lambda = 0.00045725; f =     69583657.9221866
lambda = 0.00015242; f =      7730322.4011194
lambda = 5.0805e-05; f =       858142.3364151
lambda = 1.6935e-05; f =        94700.7521048
lambda =  5.645e-06; f =         9917.6840519
lambda = 1.8817e-06; f =          511.7433530
lambda = 6.2723e-07; f =         -528.7335914
lambda = 2.0908e-07; f =         -642.9899862
lambda = 6.9692e-08; f =         -655.4021093
lambda = 2.3231e-08; f =         -656.6893521
lambda = 7.7435e-09; f =         -656.8062434
lambda = 2.5812e-09; f =         -656.8164793

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      6630863.5385073
lambda = -2.0908e-07; f =       732542.5830802
lambda = -6.9692e-08; f =        79603.7321213
lambda = -2.3231e-08; f =         7865.0121134
lambda = -7.7435e-09; f =          164.0507434
lambda = -2.5812e-09; f =         -601.6147576
Norm of dx 4.1108e+09
Predicted improvement:        9.974609213
lambda =          1; f =         -656.4789406
lambda =    0.33333; f =         -656.7828676
lambda =    0.11111; f =         -656.8136310
lambda =   0.037037; f =         -656.8166963
lambda =   0.012346; f =         -656.8169192
lambda =  0.0041152; f =         -654.0800523
lambda =  0.0013717; f =         -656.5310784
lambda = 0.00045725; f =         -656.7912412
lambda = 0.00015242; f =         -656.8160938
lambda = 5.0805e-05; f =         -656.8175038
Norm of dx     7.5773
Predicted improvement:        0.073852585
lambda =          1; f =         -656.8950175
Norm of dx  0.0039798
Done for param e_a =   0.1302; f = -656.8950
Predicted improvement:        0.005927390
lambda =          1; f =         -656.9010348
Norm of dx   0.003606
Done for param e_v =   0.3934; f = -656.9010
Predicted improvement:        0.000456279
lambda =          1; f =         -656.9014931
Norm of dx 0.00013872
Done for param e_g =   0.0535; f = -656.9015
Predicted improvement:        0.013118977
lambda =          1; f =         -656.9149029
Norm of dx 0.00078713
Done for param e_rer =   0.0582; f = -656.9149
Predicted improvement:        0.015853455
lambda =          1; f =         -656.9308515
Norm of dx  0.0013447
Done for param alp =   0.3350; f = -656.9309
Predicted improvement:        0.000266642
lambda =          1; f =         -656.9311201
Norm of dx 0.00011112
Done for param bet =   0.9201; f = -656.9311
Predicted improvement:        0.000759221
lambda =          1; f =         -656.9318794
Norm of dx 3.8842e-05
Done for param delt =   0.0999; f = -656.9319
Predicted improvement:        0.016002644
lambda =          1; f =         -656.9478403
Norm of dx   0.010321
Done for param sig =   2.1281; f = -656.9478
Predicted improvement:        0.003244755
lambda =          1; f =         -656.9511104
Norm of dx  0.0053098
Done for param phi1 =   1.4051; f = -656.9511
Predicted improvement:        0.016337341
lambda =          1; f =         -656.9674747
Norm of dx   0.065143
Done for param phi2 =   5.2432; f = -656.9675
Predicted improvement:        0.180524295
lambda =          1; f =         -657.1382383
Norm of dx  0.0093868
Done for param hf =   0.7095; f = -657.1382
Predicted improvement:        0.000037078
lambda =          1; f =         -657.1382753
Norm of dx 0.00075412
Done for param rhoa =   0.4079; f = -657.1383
Predicted improvement:        0.007244334
lambda =          1; f =         -657.1455318
Norm of dx   0.010094
Done for param rhov =   0.2121; f = -657.1455
Predicted improvement:        0.000081354
lambda =          1; f =         -657.1456131
Norm of dx  0.0011273
Done for param rhog =   0.5950; f = -657.1456
Predicted improvement:        0.000319427
lambda =          1; f =         -657.1459326
Norm of dx   0.002596
Done for param rhorer =   0.5106; f = -657.1459
Sequence of univariate steps!!
Actual dxnorm 0.06801
FVAL          -657.1459
Improvement   0.32901
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  5.741621e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.32059 s.
 
Iteration 15
Correct for low angle: 1.13417e-10
Predicted improvement: 800891219.336843491
lambda =          1; f = 291280714341362.3125000
lambda =    0.33333; f = 32364522504007.7734375
lambda =    0.11111; f = 3596057618384.5605469
lambda =   0.037037; f = 399561811342.2798462
lambda =   0.012346; f =  44395707679.8928757
lambda =  0.0041152; f =   4932839646.3239012
lambda =  0.0013717; f =    548087322.6038741
lambda = 0.00045725; f =     60896217.0086389
lambda = 0.00015242; f =      6765070.9558695
lambda = 5.0805e-05; f =       750898.7866839
lambda = 1.6935e-05; f =        82786.8993896
lambda =  5.645e-06; f =         8594.4292074
lambda = 1.8817e-06; f =          364.5854057
lambda = 6.2723e-07; f =         -545.3372554
lambda = 2.0908e-07; f =         -645.0937485
lambda = 6.9692e-08; f =         -655.9153790
lambda = 2.3231e-08; f =         -657.0347352
lambda = 7.7435e-09; f =         -657.1366367
lambda = 2.5812e-09; f =         -657.1455810

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      5851587.3291358
lambda = -2.0908e-07; f =       646176.6212845
lambda = -6.9692e-08; f =        70080.7496846
lambda = -2.3231e-08; f =         6831.1204978
lambda = -7.7435e-09; f =           57.0509981
lambda = -2.5812e-09; f =         -611.0729606
Norm of dx  3.862e+09
Predicted improvement:       10.142766647
lambda =          1; f =         -656.7636616
lambda =    0.33333; f =         -657.1062215
lambda =    0.11111; f =         -657.1420567
lambda =   0.037037; f =         -657.1456576
lambda =   0.012346; f =         -657.1459307
lambda =  0.0041152; f =         -653.9694310
lambda =  0.0013717; f =         -656.8115506
lambda = 0.00045725; f =         -657.1149630
lambda = 0.00015242; f =         -657.1445527
lambda = 5.0805e-05; f =         -657.1464663
Norm of dx     7.0844
Predicted improvement:        0.045483604
lambda =          1; f =         -657.1937357
Norm of dx   0.003257
Done for param e_a =   0.1334; f = -657.1937
Predicted improvement:        0.004475519
lambda =          1; f =         -657.1982698
Norm of dx  0.0031686
Done for param e_v =   0.3965; f = -657.1983
Predicted improvement:        0.000298028
lambda =          1; f =         -657.1985689
Norm of dx 0.00011249
Done for param e_g =   0.0536; f = -657.1986
Predicted improvement:        0.007865179
lambda =          1; f =         -657.2065714
Norm of dx 0.00062073
Done for param e_rer =   0.0589; f = -657.2066
Predicted improvement:        0.006730497
lambda =          1; f =         -657.2133341
Norm of dx 0.00088052
Done for param alp =   0.3341; f = -657.2133
Predicted improvement:        0.000369548
lambda =          1; f =         -657.2137047
Norm of dx 0.00013224
Done for param bet =   0.9200; f = -657.2137
Predicted improvement:        0.000763139
lambda =          1; f =         -657.2144678
Norm of dx 3.8941e-05
Done for param delt =   0.0999; f = -657.2145
Predicted improvement:        0.015470217
lambda =          1; f =         -657.2299259
Norm of dx   0.010001
Done for param sig =   2.1181; f = -657.2299
Predicted improvement:        0.003352301
lambda =          1; f =         -657.2332865
Norm of dx  0.0053794
Done for param phi1 =   1.4108; f = -657.2333
Predicted improvement:        0.010355912
lambda =          1; f =         -657.2436561
Norm of dx   0.052202
Done for param phi2 =   5.2954; f = -657.2437
Predicted improvement:        0.129337189
lambda =          1; f =         -657.3671370
Norm of dx  0.0076691
Done for param hf =   0.7171; f = -657.3671
Predicted improvement:        0.000011604
lambda =          1; f =         -657.3671486
Norm of dx 0.00042407
Done for param rhoa =   0.4074; f = -657.3671
Predicted improvement:        0.004559446
lambda =          1; f =         -657.3717090
Norm of dx  0.0079768
Done for param rhov =   0.2041; f = -657.3717
Predicted improvement:        0.000042033
lambda =          1; f =         -657.3717510
Norm of dx 0.00081038
Done for param rhog =   0.5958; f = -657.3718
Predicted improvement:        0.000183679
lambda =          1; f =         -657.3719347
Norm of dx  0.0019762
Done for param rhorer =   0.5086; f = -657.3719
Sequence of univariate steps!!
Actual dxnorm 0.054862
FVAL          -657.3719
Improvement   0.226
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.732731e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.32472 s.
 
Iteration 16
Correct for low angle: 1.68464e-10
Predicted improvement: 530618846.391413331
lambda =          1; f = 234292403276317.0937500
lambda =    0.33333; f = 26032488032518.2109375
lambda =    0.11111; f = 2892498263094.2578125
lambda =   0.037037; f = 321388559786.9710083
lambda =   0.012346; f =  35709794221.6563110
lambda =  0.0041152; f =   3967739278.0826554
lambda =  0.0013717; f =    440854324.0986132
lambda = 0.00045725; f =     48981564.6825072
lambda = 0.00015242; f =      5441262.4828717
lambda = 5.0805e-05; f =       603822.9103311
lambda = 1.6935e-05; f =        66449.6657321
lambda =  5.645e-06; f =         6780.3792493
lambda = 1.8817e-06; f =          163.2054988
lambda = 6.2723e-07; f =         -567.7954757
lambda = 2.0908e-07; f =         -647.7426728
lambda = 6.9692e-08; f =         -656.3936819
lambda = 2.3231e-08; f =         -657.2832733
lambda = 7.7435e-09; f =         -657.3646281
lambda = 2.5812e-09; f =         -657.3717043

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      4788746.6446271
lambda = -2.0908e-07; f =       528409.1091119
lambda = -6.9692e-08; f =        57103.9706618
lambda = -2.3231e-08; f =         5425.2894987
lambda = -7.7435e-09; f =          -87.2759815
lambda = -2.5812e-09; f =         -623.2844701
Norm of dx 3.4942e+09
Predicted improvement:       10.149082711
lambda =          1; f =         -656.9539468
lambda =    0.33333; f =         -657.3280101
lambda =    0.11111; f =         -657.3676200
lambda =   0.037037; f =         -657.3716206
lambda =   0.012346; f =         -657.3719317
lambda =  0.0041152; f =         -653.8640417
lambda =  0.0013717; f =         -657.0007432
lambda = 0.00045725; f =         -657.3368790
lambda = 0.00015242; f =         -657.3701021
lambda = 5.0805e-05; f =         -657.3724186
Norm of dx     7.1888
Predicted improvement:        0.027180557
lambda =          1; f =         -657.4004312
Norm of dx  0.0026038
Done for param e_a =   0.1360; f = -657.4004
Predicted improvement:        0.003468936
lambda =          1; f =         -657.4039405
Norm of dx  0.0028161
Done for param e_v =   0.3994; f = -657.4039
Predicted improvement:        0.000200723
lambda =          1; f =         -657.4041418
Norm of dx 9.2565e-05
Done for param e_g =   0.0537; f = -657.4041
Predicted improvement:        0.004585943
lambda =          1; f =         -657.4087892
Norm of dx 0.00048092
Done for param e_rer =   0.0593; f = -657.4088
Predicted improvement:        0.002306748
lambda =          1; f =         -657.4111019
Norm of dx 0.00051769
Done for param alp =   0.3336; f = -657.4111
Predicted improvement:        0.000386929
lambda =          1; f =         -657.4114895
Norm of dx  0.0001363
Done for param bet =   0.9199; f = -657.4115
Predicted improvement:        0.000749966
lambda =          1; f =         -657.4122395
Norm of dx 3.8602e-05
Done for param delt =   0.0999; f = -657.4122
Predicted improvement:        0.013529960
lambda =          1; f =         -657.4257685
Norm of dx   0.009238
Done for param sig =   2.1089; f = -657.4258
Predicted improvement:        0.003214952
lambda =          1; f =         -657.4289952
Norm of dx  0.0052392
Done for param phi1 =   1.4164; f = -657.4290
Predicted improvement:        0.006395555
lambda =          1; f =         -657.4353973
Norm of dx   0.041235
Done for param phi2 =   5.3366; f = -657.4354
Predicted improvement:        0.089643515
lambda =          1; f =         -657.5216961
Norm of dx  0.0061952
Done for param hf =   0.7233; f = -657.5217
Predicted improvement:        0.002684537
lambda =          1; f =         -657.5243791
Norm of dx  0.0060946
Done for param rhov =   0.1980; f = -657.5244
Predicted improvement:        0.000019594
lambda =          1; f =         -657.5243987
Norm of dx 0.00055335
Done for param rhog =   0.5964; f = -657.5244
Predicted improvement:        0.000105594
lambda =          1; f =         -657.5245043
Norm of dx  0.0015028
Done for param rhorer =   0.5071; f = -657.5245
Sequence of univariate steps!!
Actual dxnorm 0.043715
FVAL          -657.5245
Improvement   0.15257
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.888095e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.33905 s.
 
Iteration 17
Correct for low angle: 2.49447e-10
Predicted improvement: 350073922.855774760
lambda =          1; f = 190913817175663.3437500
lambda =    0.33333; f = 21212645197897.0429688
lambda =    0.11111; f = 2356960192175.2705078
lambda =   0.037037; f = 261884336956.8305664
lambda =   0.012346; f =  29098216330.9227257
lambda =  0.0041152; f =   3233120320.0910993
lambda =  0.0013717; f =    359230264.3847448
lambda = 0.00045725; f =     39912314.0844337
lambda = 0.00015242; f =      4433597.4896026
lambda = 5.0805e-05; f =       491869.7266486
lambda = 1.6935e-05; f =        54013.2987558
lambda =  5.645e-06; f =         5399.3000046
lambda = 1.8817e-06; f =            9.9035429
lambda = 6.2723e-07; f =         -584.8773137
lambda = 2.0908e-07; f =         -649.7372443
lambda = 6.9692e-08; f =         -656.7361967
lambda = 2.3231e-08; f =         -657.4521248
lambda = 7.7435e-09; f =         -657.5186844
lambda = 2.5812e-09; f =         -657.5243557

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      4017721.5741047
lambda = -2.0908e-07; f =       442999.4660865
lambda = -6.9692e-08; f =        47700.5253900
lambda = -2.3231e-08; f =         4409.2106896
lambda = -7.7435e-09; f =         -190.6817394
lambda = -2.5812e-09; f =         -631.7004784
Norm of dx 3.2011e+09
Predicted improvement:        9.823227018
lambda =          1; f =         -657.1094824
lambda =    0.33333; f =         -657.4811913
lambda =    0.11111; f =         -657.5202539
lambda =   0.037037; f =         -657.5241961
lambda =   0.012346; f =         -657.5245015
lambda =  0.0041152; f =         -654.0662343
lambda =  0.0013717; f =         -657.1582288
lambda = 0.00045725; f =         -657.4897961
lambda = 0.00015242; f =         -657.5226441
lambda = 5.0805e-05; f =         -657.5249630
Norm of dx     6.8773
Predicted improvement:        0.015836276
lambda =          1; f =         -657.5411840
Norm of dx  0.0020398
Done for param e_a =   0.1381; f = -657.5412
Predicted improvement:        0.002648928
lambda =          1; f =         -657.5438599
Norm of dx  0.0024818
Done for param e_v =   0.4018; f = -657.5439
Predicted improvement:        0.000137093
lambda =          1; f =         -657.5439973
Norm of dx 7.6666e-05
Done for param e_g =   0.0538; f = -657.5440
Predicted improvement:        0.002663305
lambda =          1; f =         -657.5466881
Norm of dx 0.00037059
Done for param e_rer =   0.0597; f = -657.5467
Predicted improvement:        0.000541793
lambda =          1; f =         -657.5472305
Norm of dx  0.0002516
Done for param alp =   0.3333; f = -657.5472
Predicted improvement:        0.000346644
lambda =          1; f =         -657.5475778
Norm of dx 0.00012966
Done for param bet =   0.9198; f = -657.5476
Predicted improvement:        0.000681554
lambda =          1; f =         -657.5482594
Norm of dx 3.6799e-05
Done for param delt =   0.0999; f = -657.5483
Predicted improvement:        0.010920358
lambda =          1; f =         -657.5591664
Norm of dx  0.0082199
Done for param sig =   2.1006; f = -657.5592
Predicted improvement:        0.002901623
lambda =          1; f =         -657.5620696
Norm of dx  0.0049659
Done for param phi1 =   1.4217; f = -657.5621
Predicted improvement:        0.003852879
lambda =          1; f =         -657.5659256
Norm of dx   0.032134
Done for param phi2 =   5.3687; f = -657.5659
Predicted improvement:        0.060537348
lambda =          1; f =         -657.6246242
Norm of dx  0.0049646
Done for param hf =   0.7283; f = -657.6246
Predicted improvement:        0.001560742
lambda =          1; f =         -657.6261835
Norm of dx  0.0046283
Done for param rhov =   0.1934; f = -657.6262
Predicted improvement:        0.000061224
lambda =          1; f =         -657.6262448
Norm of dx  0.0011469
Done for param rhorer =   0.5059; f = -657.6262
Sequence of univariate steps!!
Actual dxnorm 0.034437
FVAL          -657.6262
Improvement   0.10174
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.793458e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31449 s.
 
Iteration 18
Correct for low angle: 3.78886e-10
Predicted improvement: 229218976.955903143
lambda =          1; f = 154350802895206.8750000
lambda =    0.33333; f = 17150088099298.1972656
lambda =    0.11111; f = 1905564973555.5998535
lambda =   0.037037; f = 211729317518.4361877
lambda =   0.012346; f =  23525438010.9042511
lambda =  0.0041152; f =   2613923268.1924152
lambda =  0.0013717; f =    290430771.7105637
lambda = 0.00045725; f =     32267985.9672155
lambda = 0.00015242; f =      3584247.7287589
lambda = 5.0805e-05; f =       397504.2716013
lambda = 1.6935e-05; f =        43530.5468932
lambda =  5.645e-06; f =         4235.2487269
lambda = 1.8817e-06; f =         -119.2698746
lambda = 6.2723e-07; f =         -599.2422955
lambda = 2.0908e-07; f =         -651.3879173
lambda = 6.9692e-08; f =         -656.9959717
lambda = 2.3231e-08; f =         -657.5672557
lambda = 7.7435e-09; f =         -657.6216703
lambda = 2.5812e-09; f =         -657.6261569

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      3410994.4067499
lambda = -2.0908e-07; f =       375807.9217691
lambda = -6.9692e-08; f =        40308.9361428
lambda = -2.3231e-08; f =         3612.5757358
lambda = -7.7435e-09; f =         -271.0397005
lambda = -2.5812e-09; f =         -637.9704310
Norm of dx 2.9499e+09
Predicted improvement:        5.122036473
lambda =          1; f =         -657.4461493
lambda =    0.33333; f =         -657.6147134
lambda =    0.11111; f =         -657.6252453
lambda =   0.037037; f =         -657.6262043
lambda =   0.012346; f =         -648.8220808
lambda =  0.0041152; f =         -656.6761487
lambda =  0.0013717; f =         -657.5300478
lambda = 0.00045725; f =         -657.6186790
lambda = 0.00015242; f =         -657.6264450
lambda = 5.0805e-05; f =         -657.6266140
lambda = 9.8216e-05; f =         -657.6266857
Norm of dx     3.3936
Predicted improvement:        0.009203712
lambda =          1; f =         -657.6360606
Norm of dx  0.0015871
Done for param e_a =   0.1397; f = -657.6361
Predicted improvement:        0.001929522
lambda =          1; f =         -657.6380070
Norm of dx  0.0021342
Done for param e_v =   0.4040; f = -657.6380
Predicted improvement:        0.000096864
lambda =          1; f =         -657.6381040
Norm of dx 6.4557e-05
Done for param e_g =   0.0539; f = -657.6381
Predicted improvement:        0.001558167
lambda =          1; f =         -657.6396745
Norm of dx 0.00028588
Done for param e_rer =   0.0600; f = -657.6397
Predicted improvement:        0.000036509
lambda =          1; f =         -657.6397110
Norm of dx 6.5432e-05
Done for param alp =   0.3332; f = -657.6397
Predicted improvement:        0.000275252
lambda =          1; f =         -657.6399868
Norm of dx 0.00011599
Done for param bet =   0.9197; f = -657.6400
Predicted improvement:        0.000667069
lambda =          1; f =         -657.6406539
Norm of dx 3.6405e-05
Done for param delt =   0.0999; f = -657.6407
Predicted improvement:        0.008231418
lambda =          1; f =         -657.6488767
Norm of dx  0.0070751
Done for param sig =   2.0934; f = -657.6489
Predicted improvement:        0.002475600
lambda =          1; f =         -657.6513569
Norm of dx  0.0045699
Done for param phi1 =   1.4266; f = -657.6514
Predicted improvement:        0.002254158
lambda =          1; f =         -657.6536124
Norm of dx   0.024656
Done for param phi2 =   5.3935; f = -657.6536
Predicted improvement:        0.039734351
lambda =          1; f =         -657.6923778
Norm of dx  0.0039395
Done for param hf =   0.7323; f = -657.6924
Predicted improvement:        0.000892690
lambda =          1; f =         -657.6932696
Norm of dx   0.003488
Done for param rhov =   0.1899; f = -657.6933
Predicted improvement:        0.000021336
lambda =          1; f =         -657.6932910
Norm of dx 0.00057759
Done for param rhog =   0.5970; f = -657.6933
Predicted improvement:        0.000037052
lambda =          1; f =         -657.6933280
Norm of dx 0.00089372
Done for param rhorer =   0.5050; f = -657.6933
Sequence of univariate steps!!
Actual dxnorm 0.026921
FVAL          -657.6933
Improvement   0.067083
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.153411e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.47382 s.
 
Iteration 19
Correct for low angle: 5.71845e-10
Predicted improvement: 150930468.532816708
lambda =          1; f = 124824991522956.5468750
lambda =    0.33333; f = 13869442432193.6308594
lambda =    0.11111; f = 1541048801962.8786621
lambda =   0.037037; f = 171227525221.9028320
lambda =   0.012346; f =  19025240382.6080360
lambda =  0.0041152; f =   2113901814.8094683
lambda =  0.0013717; f =    234873000.9456589
lambda = 0.00045725; f =     26094956.5369656
lambda = 0.00015242; f =      2898374.3475442
lambda = 5.0805e-05; f =       321302.4266419
lambda = 1.6935e-05; f =        35065.8817178
lambda =  5.645e-06; f =         3295.4128066
lambda = 1.8817e-06; f =         -223.5187866
lambda = 6.2723e-07; f =         -610.8124067
lambda = 2.0908e-07; f =         -652.7006227
lambda = 6.9692e-08; f =         -657.1884073
lambda = 2.3231e-08; f =         -657.6453243
lambda = 7.7435e-09; f =         -657.6897646
lambda = 2.5812e-09; f =         -657.6932820

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2950570.8603074
lambda = -2.0908e-07; f =       324832.2533940
lambda = -6.9692e-08; f =        34705.7713418
lambda = -2.3231e-08; f =         3010.2285119
lambda = -7.7435e-09; f =         -331.2648283
lambda = -2.5812e-09; f =         -642.4677461
Norm of dx  2.744e+09
Predicted improvement:        8.724041309
lambda =          1; f =         -657.2664109
lambda =    0.33333; f =         -657.6486654
lambda =    0.11111; f =         -657.6889373
lambda =   0.037037; f =         -657.6930074
lambda =   0.012346; f =         -657.6933248
lambda =  0.0041152; f =         -654.1024016
lambda =  0.0013717; f =         -657.3103041
lambda = 0.00045725; f =         -657.6560889
lambda = 0.00015242; f =         -657.6909633
lambda = 5.0805e-05; f =         -657.6936563
Norm of dx     8.8322
Predicted improvement:        0.005266881
lambda =          1; f =         -657.6989983
Norm of dx  0.0012194
Done for param e_a =   0.1409; f = -657.6990
Predicted improvement:        0.001364237
lambda =          1; f =         -657.7003726
Norm of dx  0.0018064
Done for param e_v =   0.4058; f = -657.7004
Predicted improvement:        0.000065607
lambda =          1; f =         -657.7004383
Norm of dx 5.3211e-05
Done for param e_g =   0.0539; f = -657.7004
Predicted improvement:        0.000936699
lambda =          1; f =         -657.7013807
Norm of dx 0.00022309
Done for param e_rer =   0.0602; f = -657.7014
Predicted improvement:        0.000020872
lambda =          1; f =         -657.7014016
Norm of dx 4.9531e-05
Done for param alp =   0.3333; f = -657.7014
Predicted improvement:        0.000201587
lambda =          1; f =         -657.7016035
Norm of dx 9.9565e-05
Done for param bet =   0.9196; f = -657.7016
Predicted improvement:        0.000618752
lambda =          1; f =         -657.7022222
Norm of dx 3.5061e-05
Done for param delt =   0.0999; f = -657.7022
Predicted improvement:        0.005873842
lambda =          1; f =         -657.7080949
Norm of dx  0.0059329
Done for param sig =   2.0875; f = -657.7081
Predicted improvement:        0.001894279
lambda =          1; f =         -657.7099929
Norm of dx  0.0039883
Done for param phi1 =   1.4310; f = -657.7100
Predicted improvement:        0.001286147
lambda =          1; f =         -657.7112796
Norm of dx   0.018669
Done for param phi2 =   5.4123; f = -657.7113
Predicted improvement:        0.025359062
lambda =          1; f =         -657.7361484
Norm of dx  0.0030946
Done for param hf =   0.7354; f = -657.7361
Predicted improvement:        0.000498877
lambda =          1; f =         -657.7366469
Norm of dx     0.0026
Done for param rhov =   0.1872; f = -657.7366
Predicted improvement:        0.000022534
lambda =          1; f =         -657.7366694
Norm of dx 0.00069785
Done for param rhorer =   0.5043; f = -657.7367
Sequence of univariate steps!!
Actual dxnorm 0.020751
FVAL          -657.7367
Improvement   0.043341
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.596972e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.32546 s.
 
Iteration 20
Correct for low angle: 8.46966e-10
Predicted improvement: 100524915.478359893
lambda =          1; f = 99550240332920.4687500
lambda =    0.33333; f = 11061136785478.7500000
lambda =    0.11111; f = 1229014854905.7568359
lambda =   0.037037; f = 136557091223.0066986
lambda =   0.012346; f =  15172971459.3027802
lambda =  0.0041152; f =   1685872441.4621446
lambda =  0.0013717; f =    187314350.7071940
lambda = 0.00045725; f =     20810718.4398320
lambda = 0.00015242; f =      2311255.6082248
lambda = 5.0805e-05; f =       256073.3225980
lambda = 1.6935e-05; f =        27820.4170759
lambda =  5.645e-06; f =         2491.0411542
lambda = 1.8817e-06; f =         -312.7040082
lambda = 6.2723e-07; f =         -620.6895260
lambda = 2.0908e-07; f =         -653.8059101
lambda = 6.9692e-08; f =         -657.3372328
lambda = 2.3231e-08; f =         -657.6984177
lambda = 7.7435e-09; f =         -657.7339899
lambda = 2.5812e-09; f =         -657.7366519

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2595172.1058800
lambda = -2.0908e-07; f =       285494.3631439
lambda = -6.9692e-08; f =        30385.1593490
lambda = -2.3231e-08; f =         2546.8900235
lambda = -7.7435e-09; f =         -377.1960364
lambda = -2.5812e-09; f =         -645.7465943
Norm of dx 2.5738e+09
Predicted improvement:        4.180085301
lambda =          1; f =         -657.6319501
lambda =    0.33333; f =         -657.7259190
lambda =    0.11111; f =         -657.7357466
lambda =   0.037037; f =         -657.7366341
lambda =   0.012346; f =         -649.4087321
lambda =  0.0041152; f =         -656.8343312
lambda =  0.0013717; f =         -657.6440563
lambda = 0.00045725; f =         -657.7289276
lambda = 0.00015242; f =         -657.7366587
lambda = 5.0805e-05; f =         -657.7369514
Norm of dx     6.0279
Predicted improvement:        0.003007664
lambda =          1; f =         -657.7399917
Norm of dx 0.00093254
Done for param e_a =   0.1418; f = -657.7400
Predicted improvement:        0.000929782
lambda =          1; f =         -657.7409272
Norm of dx  0.0014998
Done for param e_v =   0.4073; f = -657.7409
Predicted improvement:        0.000049832
lambda =          1; f =         -657.7409771
Norm of dx  4.643e-05
Done for param e_g =   0.0540; f = -657.7410
Predicted improvement:        0.000583019
lambda =          1; f =         -657.7415630
Norm of dx 0.00017687
Done for param e_rer =   0.0604; f = -657.7416
Predicted improvement:        0.000113219
lambda =          1; f =         -657.7416761
Norm of dx 0.00011544
Done for param alp =   0.3334; f = -657.7417
Predicted improvement:        0.000134532
lambda =          1; f =         -657.7418108
Norm of dx 8.1526e-05
Done for param bet =   0.9195; f = -657.7418
Predicted improvement:        0.000165322
lambda =          1; f =         -657.7419761
Norm of dx 1.8123e-05
Done for param delt =   0.0999; f = -657.7420
Predicted improvement:        0.004016513
lambda =          1; f =         -657.7459903
Norm of dx  0.0048798
Done for param sig =   2.0826; f = -657.7460
Predicted improvement:        0.001437334
lambda =          1; f =         -657.7474305
Norm of dx   0.003468
Done for param phi1 =   1.4347; f = -657.7474
Predicted improvement:        0.000738027
lambda =          1; f =         -657.7481688
Norm of dx   0.014167
Done for param phi2 =   5.4267; f = -657.7482
Predicted improvement:        0.015994630
lambda =          1; f =         -657.7639196
Norm of dx  0.0024248
Done for param hf =   0.7378; f = -657.7639
Predicted improvement:        0.000280606
lambda =          1; f =         -657.7642000
Norm of dx  0.0019455
Done for param rhov =   0.1853; f = -657.7642
Predicted improvement:        0.000014641
lambda =          1; f =         -657.7642147
Norm of dx 0.00056304
Done for param rhorer =   0.5037; f = -657.7642
Sequence of univariate steps!!
Actual dxnorm 0.016046
FVAL          -657.7642
Improvement   0.027545
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.125189e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31444 s.
 
Iteration 21
Correct for low angle: 1.27201e-09
Predicted improvement: 67249378.743744001
lambda =          1; f = 76116051392276.8281250
lambda =    0.33333; f = 8457338065928.6787109
lambda =    0.11111; f = 939703903277.7421875
lambda =   0.037037; f = 104411435667.9965210
lambda =   0.012346; f =  11601233865.5516548
lambda =  0.0041152; f =   1289013346.3074841
lambda =  0.0013717; f =    143219108.2154411
lambda = 0.00045725; f =     15911317.9243170
lambda = 0.00015242; f =      1766901.4279671
lambda = 5.0805e-05; f =       195597.4403717
lambda = 1.6935e-05; f =        21103.5708415
lambda =  5.645e-06; f =         1745.5474560
lambda = 1.8817e-06; f =         -395.2845295
lambda = 6.2723e-07; f =         -629.8015829
lambda = 2.0908e-07; f =         -654.8097535
lambda = 6.9692e-08; f =         -657.4605940
lambda = 2.3231e-08; f =         -657.7354414
lambda = 7.7435e-09; f =         -657.7623775
lambda = 2.5812e-09; f =         -657.7642131

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2288767.5389799
lambda = -2.0908e-07; f =       251588.0108652
lambda = -6.9692e-08; f =        26663.9739872
lambda = -2.3231e-08; f =         2148.8045244
lambda = -7.7435e-09; f =         -416.3175142
lambda = -2.5812e-09; f =         -648.4062964
Norm of dx 2.4174e+09
Predicted improvement:        3.618534056
lambda =          1; f =         -657.6683850
lambda =    0.33333; f =         -657.7544130
lambda =    0.11111; f =         -657.7633843
lambda =   0.037037; f =         -657.7641853
lambda =   0.012346; f =         -650.0646147
lambda =  0.0041152; f =         -656.9286152
lambda =  0.0013717; f =         -657.6779900
lambda = 0.00045725; f =         -657.7568403
lambda = 0.00015242; f =         -657.7641306
lambda = 5.0805e-05; f =         -657.7644504
Norm of dx     7.5858
Predicted improvement:        0.001705409
lambda =          1; f =         -657.7661699
Norm of dx  0.0007086
Done for param e_a =   0.1425; f = -657.7662
Predicted improvement:        0.000617493
lambda =          1; f =         -657.7667904
Norm of dx  0.0012281
Done for param e_v =   0.4085; f = -657.7668
Predicted improvement:        0.000035960
lambda =          1; f =         -657.7668264
Norm of dx 3.9483e-05
Done for param e_g =   0.0540; f = -657.7668
Predicted improvement:        0.000378093
lambda =          1; f =         -657.7672060
Norm of dx 0.00014298
Done for param e_rer =   0.0605; f = -657.7672
Predicted improvement:        0.000187020
lambda =          1; f =         -657.7673929
Norm of dx 0.00014841
Done for param alp =   0.3335; f = -657.7674
Predicted improvement:        0.000081326
lambda =          1; f =         -657.7674743
Norm of dx 6.3493e-05
Done for param bet =   0.9195; f = -657.7675
Predicted improvement:        0.000142995
lambda =          1; f =         -657.7676173
Norm of dx 1.6855e-05
Done for param delt =   0.0999; f = -657.7676
Predicted improvement:        0.002666903
lambda =          1; f =         -657.7702835
Norm of dx  0.0039582
Done for param sig =   2.0787; f = -657.7703
Predicted improvement:        0.001026358
lambda =          1; f =         -657.7713115
Norm of dx  0.0029275
Done for param phi1 =   1.4379; f = -657.7713
Predicted improvement:        0.000398947
lambda =          1; f =         -657.7717105
Norm of dx   0.010431
Done for param phi2 =   5.4374; f = -657.7717
Predicted improvement:        0.009892542
lambda =          1; f =         -657.7814852
Norm of dx  0.0018867
Done for param hf =   0.7397; f = -657.7815
Predicted improvement:        0.000011463
lambda =          1; f =         -657.7814967
Norm of dx 0.00042836
Done for param rhoa =   0.4079; f = -657.7815
Predicted improvement:        0.000141770
lambda =          1; f =         -657.7816384
Norm of dx  0.0013804
Done for param rhov =   0.1839; f = -657.7816
Sequence of univariate steps!!
Actual dxnorm 0.012179
FVAL          -657.7816
Improvement   0.017424
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.662972e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.28738 s.
 
Iteration 22
Correct for low angle: 1.81218e-09
Predicted improvement: 47130523.483246818
lambda =          1; f = 60093352892483.6562500
lambda =    0.33333; f = 6677038227918.7695312
lambda =    0.11111; f = 741892808600.3745117
lambda =   0.037037; f =  82432424627.9353333
lambda =   0.012346; f =   9159121355.6807003
lambda =  0.0041152; f =   1017667455.8800915
lambda =  0.0013717; f =    113069547.5336961
lambda = 0.00045725; f =     12561362.3353206
lambda = 0.00015242; f =      1394684.0377610
lambda = 5.0805e-05; f =       154241.2832299
lambda = 1.6935e-05; f =        16510.1250936
lambda =  5.645e-06; f =         1235.8759235
lambda = 1.8817e-06; f =         -451.6863640
lambda = 6.2723e-07; f =         -636.0059883
lambda = 2.0908e-07; f =         -655.4888862
lambda = 6.9692e-08; f =         -657.5437258
lambda = 2.3231e-08; f =         -657.7596380
lambda = 7.7435e-09; f =         -657.7803821
lambda = 2.5812e-09; f =         -650.0846933

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2084174.8754591
lambda = -2.0908e-07; f =       228953.2798980
lambda = -6.9692e-08; f =        24181.5915460
lambda = -2.3231e-08; f =         1883.8363649
lambda = -7.7435e-09; f =         -442.1514578
lambda = -2.5812e-09; f =         -650.0846932
Norm of dx 2.3071e+09
Predicted improvement:        3.691713336
lambda =          1; f =         -657.6311607
lambda =    0.33333; f =         -657.7659835
lambda =    0.11111; f =         -657.7802306
lambda =   0.037037; f =         -657.7815691
lambda =   0.012346; f =         -645.4977955
lambda =  0.0041152; f =         -656.4371927
lambda =  0.0013717; f =         -657.6390116
lambda = 0.00045725; f =         -657.7680418
lambda = 0.00015242; f =         -657.7808779
lambda = 5.0805e-05; f =         -657.7818040
Norm of dx     12.525
Predicted improvement:        0.000926688
lambda =          1; f =         -657.7827363
Norm of dx 0.00052596
Done for param e_a =   0.1430; f = -657.7827
Predicted improvement:        0.000419719
lambda =          1; f =         -657.7831578
Norm of dx  0.0010164
Done for param e_v =   0.4096; f = -657.7832
Predicted improvement:        0.000027301
lambda =          1; f =         -657.7831851
Norm of dx 3.4433e-05
Done for param e_g =   0.0540; f = -657.7832
Predicted improvement:        0.000253328
lambda =          1; f =         -657.7834392
Norm of dx 0.00011739
Done for param e_rer =   0.0607; f = -657.7834
Predicted improvement:        0.000190458
lambda =          1; f =         -657.7836296
Norm of dx 0.00014977
Done for param alp =   0.3337; f = -657.7836
Predicted improvement:        0.000045661
lambda =          1; f =         -657.7836752
Norm of dx 4.7633e-05
Done for param bet =   0.9194; f = -657.7837
Predicted improvement:        0.000210318
lambda =          1; f =         -657.7838856
Norm of dx 2.0441e-05
Done for param delt =   0.0999; f = -657.7839
Predicted improvement:        0.001729043
lambda =          1; f =         -657.7856141
Norm of dx  0.0031764
Done for param sig =   2.0756; f = -657.7856
Predicted improvement:        0.000653327
lambda =          1; f =         -657.7862683
Norm of dx   0.002334
Done for param phi1 =   1.4406; f = -657.7863
Predicted improvement:        0.000197358
lambda =          1; f =         -657.7864657
Norm of dx  0.0073438
Done for param phi2 =   5.4452; f = -657.7865
Predicted improvement:        0.006002876
lambda =          1; f =         -657.7924133
Norm of dx  0.0014574
Done for param hf =   0.7412; f = -657.7924
Predicted improvement:        0.000081859
lambda =          1; f =         -657.7924951
Norm of dx  0.0010477
Done for param rhov =   0.1829; f = -657.7925
Predicted improvement:        0.000032469
lambda =          1; f =         -657.7925276
Norm of dx 0.00083955
Done for param rhorer =   0.5029; f = -657.7925
Sequence of univariate steps!!
Actual dxnorm 0.0091316
FVAL          -657.7925
Improvement   0.010889
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.103923e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.23416 s.
 
Iteration 23
Correct for low angle: 2.52885e-09
Predicted improvement: 33393438.016488634
lambda =          1; f = 43866997355927.5000000
lambda =    0.33333; f = 4874109964785.0478516
lambda =    0.11111; f = 541567489301.3606567
lambda =   0.037037; f =  60174070239.4326096
lambda =   0.012346; f =   6685975674.2676630
lambda =  0.0041152; f =    742875092.0435498
lambda =  0.0013717; f =     82537594.9500525
lambda = 0.00045725; f =      9169099.2871690
lambda = 0.00015242; f =      1017823.3185880
lambda = 5.0805e-05; f =       112385.6815108
lambda = 1.6935e-05; f =        11864.1195041
lambda =  5.645e-06; f =          721.0178623
lambda = 1.8817e-06; f =         -508.4517815
lambda = 6.2723e-07; f =         -642.1752661
lambda = 2.0908e-07; f =         -656.1442605
lambda = 6.9692e-08; f =         -657.6215338
lambda = 2.3231e-08; f =         -657.7772859
lambda = 7.7435e-09; f =         -657.7918016
lambda = 2.5812e-09; f =         -651.7275603

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1871236.3466004
lambda = -2.0908e-07; f =       205400.4846927
lambda = -6.9692e-08; f =        21600.2856552
lambda = -2.3231e-08; f =         1608.9084943
lambda = -7.7435e-09; f =         -468.7441295
lambda = -2.5812e-09; f =         -651.7275603
Norm of dx 2.1864e+09
Predicted improvement:        2.333739509
lambda =          1; f =         -657.7234223
lambda =    0.33333; f =         -657.7855652
lambda =    0.11111; f =         -657.7919693
lambda =   0.037037; f =         -657.7925139
lambda =   0.012346; f =         -652.0796348
lambda =  0.0041152; f =         -657.1706170
lambda =  0.0013717; f =         -657.7276961
lambda = 0.00045725; f =         -657.7867469
lambda = 0.00015242; f =         -657.7923595
lambda = 5.0805e-05; f =         -657.7926670
Norm of dx     9.5851
Predicted improvement:        0.000550724
lambda =          1; f =         -657.7932203
Norm of dx 0.00040748
Done for param e_a =   0.1434; f = -657.7932
Predicted improvement:        0.000254702
lambda =          1; f =         -657.7934758
Norm of dx 0.00079446
Done for param e_v =   0.4104; f = -657.7935
Predicted improvement:        0.000020841
lambda =          1; f =         -657.7934967
Norm of dx 3.0108e-05
Done for param e_g =   0.0541; f = -657.7935
Predicted improvement:        0.000171985
lambda =          1; f =         -657.7936691
Norm of dx 9.6961e-05
Done for param e_rer =   0.0608; f = -657.7937
Predicted improvement:        0.000181447
lambda =          1; f =         -657.7938504
Norm of dx 0.00014618
Done for param alp =   0.3338; f = -657.7939
Predicted improvement:        0.000023491
lambda =          1; f =         -657.7938739
Norm of dx 3.4195e-05
Done for param bet =   0.9194; f = -657.7939
Predicted improvement:        0.000097274
lambda =          1; f =         -657.7939712
Norm of dx 1.3901e-05
Done for param delt =   0.0999; f = -657.7940
Predicted improvement:        0.001061686
lambda =          1; f =         -657.7950326
Norm of dx  0.0024824
Done for param sig =   2.0732; f = -657.7950
Predicted improvement:        0.000418387
lambda =          1; f =         -657.7954514
Norm of dx  0.0018669
Done for param phi1 =   1.4428; f = -657.7955
Predicted improvement:        0.000106294
lambda =          1; f =         -657.7955577
Norm of dx  0.0053935
Done for param phi2 =   5.4510; f = -657.7956
Predicted improvement:        0.003592846
lambda =          1; f =         -657.7991252
Norm of dx  0.0011202
Done for param hf =   0.7423; f = -657.7991
Predicted improvement:        0.000047054
lambda =          1; f =         -657.7991722
Norm of dx 0.00079352
Done for param rhov =   0.1821; f = -657.7992
Sequence of univariate steps!!
Actual dxnorm 0.0068379
FVAL          -657.7992
Improvement   0.0066447
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.009930e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31949 s.
 
Iteration 24
Correct for low angle: 3.25193e-09
Predicted improvement: 25971443.568382844
lambda =          1; f = 37005180983300.2343750
lambda =    0.33333; f = 4111685952396.7983398
lambda =    0.11111; f = 456853719819.5592651
lambda =   0.037037; f =  50761432411.2835617
lambda =   0.012346; f =   5640128103.0588188
lambda =  0.0041152; f =    626670166.3765472
lambda =  0.0013717; f =     69626057.7853433
lambda = 0.00045725; f =      7734525.6960033
lambda = 0.00015242; f =       858441.3818969
lambda = 5.0805e-05; f =        94682.8615373
lambda = 1.6935e-05; f =         9900.0204277
lambda =  5.645e-06; f =          503.8517377
lambda = 1.8817e-06; f =         -532.2316063
lambda = 6.2723e-07; f =         -644.7068447
lambda = 2.0908e-07; f =         -656.4124477
lambda = 6.9692e-08; f =         -657.6560795
lambda = 2.3231e-08; f =         -657.7866448
lambda = 7.7435e-09; f =         -657.7986253
lambda = 2.5812e-09; f =         -652.6910448

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1738946.3440814
lambda = -2.0908e-07; f =       190771.2127031
lambda = -6.9692e-08; f =        19998.0073041
lambda = -2.3231e-08; f =         1438.6050659
lambda = -7.7435e-09; f =         -485.0951314
lambda = -2.5812e-09; f =         -652.6910448
Norm of dx 2.1079e+09
Predicted improvement:        1.718203117
lambda =          1; f =         -657.7468391
lambda =    0.33333; f =         -657.7939783
lambda =    0.11111; f =         -657.7987787
lambda =   0.037037; f =         -657.7991663
lambda =   0.012346; f =         -653.3840829
lambda =  0.0041152; f =         -657.3180732
lambda =  0.0013717; f =         -657.7488604
lambda = 0.00045725; f =         -657.7946296
lambda = 0.00015242; f =         -657.7990167
lambda = 5.0805e-05; f =         -657.7992713
Norm of dx     9.8451
Predicted improvement:        0.000320560
lambda =          1; f =         -657.7995931
Norm of dx 0.00031208
Done for param e_a =   0.1437; f = -657.7996
Predicted improvement:        0.000162029
lambda =          1; f =         -657.7997555
Norm of dx 0.00063529
Done for param e_v =   0.4111; f = -657.7998
Predicted improvement:        0.000016711
lambda =          1; f =         -657.7997722
Norm of dx 2.6978e-05
Done for param e_g =   0.0541; f = -657.7998
Predicted improvement:        0.000128178
lambda =          1; f =         -657.7999007
Norm of dx 8.3869e-05
Done for param e_rer =   0.0608; f = -657.7999
Predicted improvement:        0.000132350
lambda =          1; f =         -657.8000330
Norm of dx 0.00012482
Done for param alp =   0.3340; f = -657.8000
Predicted improvement:        0.000010659
lambda =          1; f =         -657.8000436
Norm of dx 2.3048e-05
Done for param bet =   0.9194; f = -657.8000
Predicted improvement:        0.000073059
lambda =          1; f =         -657.8001167
Norm of dx 1.2047e-05
Done for param delt =   0.0999; f = -657.8001
Predicted improvement:        0.000644448
lambda =          1; f =         -657.8007610
Norm of dx  0.0019301
Done for param sig =   2.0713; f = -657.8008
Predicted improvement:        0.000254583
lambda =          1; f =         -657.8010158
Norm of dx  0.0014557
Done for param phi1 =   1.4445; f = -657.8010
Predicted improvement:        0.000056067
lambda =          1; f =         -657.8010719
Norm of dx  0.0039193
Done for param phi2 =   5.4554; f = -657.8011
Predicted improvement:        0.002133306
lambda =          1; f =         -657.8031935
Norm of dx  0.0008588
Done for param hf =   0.7432; f = -657.8032
Predicted improvement:        0.000025382
lambda =          1; f =         -657.8032189
Norm of dx 0.00058238
Done for param rhov =   0.1815; f = -657.8032
Predicted improvement:        0.000016285
lambda =          1; f =         -657.8032352
Norm of dx 0.00059509
Done for param rhorer =   0.5023; f = -657.8032
Sequence of univariate steps!!
Actual dxnorm 0.0052179
FVAL          -657.8032
Improvement   0.004063
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.484560e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.34593 s.
 
Iteration 25
Correct for low angle: 4.23747e-09
Predicted improvement: 19913174.317335732
lambda =          1; f = 31785011138606.3945312
lambda =    0.33333; f = 3531667201804.3408203
lambda =    0.11111; f = 392407232321.5194702
lambda =   0.037037; f =  43600725025.3828964
lambda =   0.012346; f =   4844498430.1674223
lambda =  0.0041152; f =    538268361.7804178
lambda =  0.0013717; f =     59804131.2089894
lambda = 0.00045725; f =      6643364.5989843
lambda = 0.00015242; f =       737254.6384069
lambda = 5.0805e-05; f =        81234.0523139
lambda = 1.6935e-05; f =         8409.7738902
lambda =  5.645e-06; f =          339.5064397
lambda = 1.8817e-06; f =         -550.0835966
lambda = 6.2723e-07; f =         -646.5581516
lambda = 2.0908e-07; f =         -656.6037681
lambda = 6.9692e-08; f =         -657.6796720
lambda = 2.3231e-08; f =         -657.7924525
lambda = 7.7435e-09; f =         -657.8027431
lambda = 2.5812e-09; f =         -657.8032347

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1626490.3708082
lambda = -2.0908e-07; f =       178337.3959911
lambda = -6.9692e-08; f =        18636.8955554
lambda = -2.3231e-08; f =         1294.1752569
lambda = -7.7435e-09; f =         -498.8772070
lambda = -2.5812e-09; f =         -653.4695580
Norm of dx 2.0388e+09
Predicted improvement:        1.227842741
lambda =          1; f =         -657.7648318
lambda =    0.33333; f =         -657.7994975
lambda =    0.11111; f =         -657.8029730
lambda =   0.037037; f =         -657.8032337
lambda =   0.012346; f =         -654.4884564
lambda =  0.0041152; f =         -657.4416915
lambda =  0.0013717; f =         -657.7653102
lambda = 0.00045725; f =         -657.7997699
lambda = 0.00015242; f =         -657.8030997
lambda = 5.0805e-05; f =         -657.8033033
Norm of dx     9.6408
Predicted improvement:        0.000187995
lambda =          1; f =         -657.8034918
Norm of dx 0.00023969
Done for param e_a =   0.1440; f = -657.8035
Predicted improvement:        0.000101030
lambda =          1; f =         -657.8035931
Norm of dx 0.00050271
Done for param e_v =   0.4116; f = -657.8036
Predicted improvement:        0.000011951
lambda =          1; f =         -657.8036050
Norm of dx 2.2828e-05
Done for param e_g =   0.0541; f = -657.8036
Predicted improvement:        0.000087854
lambda =          1; f =         -657.8036931
Norm of dx 6.9556e-05
Done for param e_rer =   0.0609; f = -657.8037
Predicted improvement:        0.000097647
lambda =          1; f =         -657.8037907
Norm of dx 0.00010719
Done for param alp =   0.3341; f = -657.8038
Predicted improvement:        0.000051656
lambda =          1; f =         -657.8038423
Norm of dx  1.013e-05
Done for param delt =   0.0999; f = -657.8038
Predicted improvement:        0.000429912
lambda =          1; f =         -657.8042722
Norm of dx   0.001574
Done for param sig =   2.0698; f = -657.8043
Predicted improvement:        0.000159203
lambda =          1; f =         -657.8044315
Norm of dx  0.0011509
Done for param phi1 =   1.4459; f = -657.8044
Predicted improvement:        0.000023322
lambda =          1; f =         -657.8044548
Norm of dx  0.0025288
Done for param phi2 =   5.4583; f = -657.8045
Predicted improvement:        0.001269481
lambda =          1; f =         -657.8057190
Norm of dx 0.00065997
Done for param hf =   0.7439; f = -657.8057
Predicted improvement:        0.000011156
lambda =          1; f =         -657.8057301
Norm of dx 0.00042376
Done for param rhoa =   0.4083; f = -657.8057
Sequence of univariate steps!!
Actual dxnorm 0.0037217
FVAL          -657.8057
Improvement   0.0024949
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.115001e-19.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31469 s.
 
Iteration 26
Correct for low angle: 4.80139e-09
Predicted improvement: 17549004.943785850
lambda =          1; f = 36592172121364.5468750
lambda =    0.33333; f = 4065796186530.7666016
lambda =    0.11111; f = 451754892839.7192383
lambda =   0.037037; f =  50194908044.9493713
lambda =   0.012346; f =   5577184939.5348520
lambda =  0.0041152; f =    619677811.0087700
lambda =  0.0013717; f =     68849572.6051228
lambda = 0.00045725; f =      7648397.3340974
lambda = 0.00015242; f =       848920.8582212
lambda = 5.0805e-05; f =        93641.0354604
lambda = 1.6935e-05; f =         9788.9725115
lambda =  5.645e-06; f =          493.0844888
lambda = 1.8817e-06; f =         -532.8913382
lambda = 6.2723e-07; f =         -644.5959387
lambda = 2.0908e-07; f =         -656.3999382
lambda = 6.9692e-08; f =         -657.6606534
lambda = 2.3231e-08; f =         -657.7927860
lambda = 7.7435e-09; f =         -657.8050801
lambda = 2.5812e-09; f =         -657.8057277

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1570618.6669909
lambda = -2.0908e-07; f =       172160.7035622
lambda = -6.9692e-08; f =        17961.0143908
lambda = -2.3231e-08; f =         1222.5464207
lambda = -7.7435e-09; f =         -505.6815275
lambda = -2.5812e-09; f =         -653.8422820
Norm of dx 2.0036e+09
Predicted improvement:        0.376761477
lambda =          1; f =         -657.8009449
lambda =    0.33333; f =         -657.8053740
lambda =    0.11111; f =         -657.8057257
lambda =   0.037037; f =         -653.6000766
lambda =   0.012346; f =         -657.3446947
lambda =  0.0041152; f =         -657.7565728
lambda =  0.0013717; f =         -657.8009574
lambda = 0.00045725; f =         -657.8054295
lambda = 0.00015242; f =         -657.8057733
Norm of dx     2.7423
Predicted improvement:        0.000101536
lambda =          1; f =         -657.8058751
Norm of dx 0.00017655
Done for param e_a =   0.1442; f = -657.8059
Predicted improvement:        0.000091337
lambda =          1; f =         -657.8059666
Norm of dx 0.00047864
Done for param e_v =   0.4121; f = -657.8060
Predicted improvement:        0.000010830
lambda =          1; f =         -657.8059774
Norm of dx 2.1741e-05
Done for param e_g =   0.0541; f = -657.8060
Predicted improvement:        0.000069875
lambda =          1; f =         -657.8060474
Norm of dx 6.2115e-05
Done for param e_rer =   0.0610; f = -657.8060
Predicted improvement:        0.000049487
lambda =          1; f =         -657.8060969
Norm of dx 7.6285e-05
Done for param alp =   0.3342; f = -657.8061
Predicted improvement:        0.000065810
lambda =          1; f =         -657.8061627
Norm of dx 1.1434e-05
Done for param delt =   0.0999; f = -657.8062
Predicted improvement:        0.000222791
lambda =          1; f =         -657.8063854
Norm of dx  0.0011318
Done for param sig =   2.0688; f = -657.8064
Predicted improvement:        0.000077781
lambda =          1; f =         -657.8064633
Norm of dx 0.00080437
Done for param phi1 =   1.4470; f = -657.8065
Predicted improvement:        0.000014691
lambda =          1; f =         -657.8064779
Norm of dx  0.0020076
Done for param phi2 =   5.4606; f = -657.8065
Predicted improvement:        0.000710264
lambda =          1; f =         -657.8071860
Norm of dx 0.00049217
Done for param hf =   0.7444; f = -657.8072
Predicted improvement:        0.000024997
lambda =          1; f =         -657.8072110
Norm of dx 0.00057776
Done for param rhov =   0.1809; f = -657.8072
Sequence of univariate steps!!
Actual dxnorm 0.0028961
FVAL          -657.8072
Improvement   0.0014809
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.702154e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.28602 s.
 
Iteration 27
Correct for low angle: 5.77996e-09
Predicted improvement: 14537210.687625036
lambda =          1; f = 41523197816667.9687500
lambda =    0.33333; f = 4613687949306.1845703
lambda =    0.11111; f = 512631761654.7918701
lambda =   0.037037; f =  56959006674.9790497
lambda =   0.012346; f =   6328752152.5212297
lambda =  0.0041152; f =    703185512.1626759
lambda =  0.0013717; f =     78128283.9462012
lambda = 0.00045725; f =      8679391.4188254
lambda = 0.00015242; f =       963484.6739352
lambda = 5.0805e-05; f =       106372.9180617
lambda = 1.6935e-05; f =        11204.5110719
lambda =  5.645e-06; f =          651.3017256
lambda = 1.8817e-06; f =         -515.0016355
lambda = 6.2723e-07; f =         -642.5186043
lambda = 2.0908e-07; f =         -656.1782107
lambda = 6.9692e-08; f =         -657.6396125
lambda = 2.3231e-08; f =         -657.7918909
lambda = 7.7435e-09; f =         -657.8063412
lambda = 2.5812e-09; f =         -657.8072011

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1502146.8360209
lambda = -2.0908e-07; f =       164591.7921194
lambda = -6.9692e-08; f =        17133.0410985
lambda = -2.3231e-08; f =         1134.8870641
lambda = -7.7435e-09; f =         -513.9767037
lambda = -2.5812e-09; f =         -654.2833377
Norm of dx 1.9595e+09
Predicted improvement:        0.224621869
lambda =          1; f =         -657.8044912
lambda =    0.33333; f =         -657.8070368
lambda =    0.11111; f =         -657.8072110
lambda =   0.037037; f =         -655.2682555
lambda =   0.012346; f =         -657.5288291
lambda =  0.0041152; f =         -657.7775129
lambda =  0.0013717; f =         -657.8043221
lambda = 0.00045725; f =         -657.8070270
lambda = 0.00015242; f =         -657.8072362
Norm of dx     2.4031
Predicted improvement:        0.000070380
lambda =          1; f =         -657.8073067
Norm of dx 0.00014721
Done for param e_a =   0.1443; f = -657.8073
Predicted improvement:        0.000027575
lambda =          1; f =         -657.8073343
Norm of dx 0.00026352
Done for param e_v =   0.4124; f = -657.8073
Predicted improvement:        0.000044775
lambda =          1; f =         -657.8073792
Norm of dx 4.9789e-05
Done for param e_rer =   0.0610; f = -657.8074
Predicted improvement:        0.000014384
lambda =          1; f =         -657.8073935
Norm of dx 4.1114e-05
Done for param alp =   0.3342; f = -657.8074
Predicted improvement:        0.000039571
lambda =          1; f =         -657.8074331
Norm of dx 8.8664e-06
Done for param delt =   0.0999; f = -657.8074
Predicted improvement:        0.000112108
lambda =          1; f =         -657.8075452
Norm of dx 0.00080222
Done for param sig =   2.0680; f = -657.8075
Predicted improvement:        0.000037380
lambda =          1; f =         -657.8075826
Norm of dx 0.00055757
Done for param phi1 =   1.4478; f = -657.8076
Predicted improvement:        0.000443589
lambda =          1; f =         -657.8080251
Norm of dx  0.0003881
Done for param hf =   0.7448; f = -657.8080
Predicted improvement:        0.000015955
lambda =          1; f =         -657.8080411
Norm of dx 0.00058953
Done for param rhorer =   0.5017; f = -657.8080
Sequence of univariate steps!!
Actual dxnorm 0.0013715
FVAL          -657.808
Improvement   0.00083007
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.056732e-19.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.2519 s.
 
Iteration 28
Correct for low angle: 6.32005e-09
Predicted improvement: 13308930.416275196
lambda =          1; f = 35630589454211.1875000
lambda =    0.33333; f = 3958953893086.4697266
lambda =    0.11111; f = 439883601937.9774170
lambda =   0.037037; f =  48875900728.1026611
lambda =   0.012346; f =   5430636899.5839834
lambda =  0.0041152; f =    603397465.0525255
lambda =  0.0013717; f =     67041561.8725686
lambda = 0.00045725; f =      7447806.1826418
lambda = 0.00015242; f =       826725.9937839
lambda = 5.0805e-05; f =        91199.8242888
lambda = 1.6935e-05; f =         9524.4670926
lambda =  5.645e-06; f =          465.8537736
lambda = 1.8817e-06; f =         -535.2003724
lambda = 6.2723e-07; f =         -644.6150820
lambda = 2.0908e-07; f =         -656.3966178
lambda = 6.9692e-08; f =         -657.6614756
lambda = 2.3231e-08; f =         -657.7944656
lambda = 7.7435e-09; f =         -657.8071686
lambda = 2.5812e-09; f =         -657.8080249

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1476973.8799744
lambda = -2.0908e-07; f =       161809.3874376
lambda = -6.9692e-08; f =        16828.7460127
lambda = -2.3231e-08; f =         1102.6935235
lambda = -7.7435e-09; f =         -517.0147821
lambda = -2.5812e-09; f =         -654.4416814
Norm of dx 1.9431e+09
Predicted improvement:        0.078387011
lambda =          1; f =         -657.8073110
lambda =    0.33333; f =         -657.8080179
lambda =    0.11111; f =         -650.8040447
lambda =   0.037037; f =         -657.0337291
lambda =   0.012346; f =         -657.7232974
lambda =  0.0041152; f =         -657.7990553
lambda =  0.0013717; f =         -657.8071860
lambda = 0.00045725; f =         -657.8079939
lambda = 0.00015242; f =         -657.8080518
Norm of dx    0.49723
Predicted improvement:        0.000034624
lambda =          1; f =         -657.8080864
Norm of dx  0.0001034
Done for param e_a =   0.1444; f = -657.8081
Predicted improvement:        0.000022892
lambda =          1; f =         -657.8081094
Norm of dx 0.00024028
Done for param e_v =   0.4126; f = -657.8081
Predicted improvement:        0.000021577
lambda =          1; f =         -657.8081310
Norm of dx 3.0693e-05
Done for param e_g =   0.0542; f = -657.8081
Predicted improvement:        0.000029635
lambda =          1; f =         -657.8081606
Norm of dx 4.0549e-05
Done for param e_rer =   0.0611; f = -657.8082
Predicted improvement:        0.000019376
lambda =          1; f =         -657.8081800
Norm of dx  4.772e-05
Done for param alp =   0.3343; f = -657.8082
Predicted improvement:        0.000013387
lambda =          1; f =         -657.8081934
Norm of dx 5.1571e-06
Done for param delt =   0.0999; f = -657.8082
Predicted improvement:        0.000065546
lambda =          1; f =         -657.8082589
Norm of dx   0.000613
Done for param sig =   2.0674; f = -657.8083
Predicted improvement:        0.000021527
lambda =          1; f =         -657.8082805
Norm of dx 0.00042309
Done for param phi1 =   1.4483; f = -657.8083
Predicted improvement:        0.000022770
lambda =          1; f =         -657.8083032
Norm of dx  0.0025001
Done for param phi2 =   5.4633; f = -657.8083
Predicted improvement:        0.000228968
lambda =          1; f =         -657.8085318
Norm of dx 0.00027831
Done for param hf =   0.7450; f = -657.8085
Predicted improvement:        0.000016304
lambda =          1; f =         -657.8085481
Norm of dx 0.00046633
Done for param rhov =   0.1804; f = -657.8085
Sequence of univariate steps!!
Actual dxnorm 0.0026964
FVAL          -657.8085
Improvement   0.00050703
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.435551e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.23363 s.
 
Iteration 29
Correct for low angle: 7.68682e-09
Predicted improvement: 10935673.109716650
lambda =          1; f = 51811454084187.5859375
lambda =    0.33333; f = 5756827668143.6943359
lambda =    0.11111; f = 639647330489.2614746
lambda =   0.037037; f =  71071862496.3239899
lambda =   0.012346; f =   7896852190.3678093
lambda =  0.0041152; f =    877420498.5701612
lambda =  0.0013717; f =     97488276.5103237
lambda = 0.00045725; f =     10830684.9206792
lambda = 0.00015242; f =      1202578.3645349
lambda = 5.0805e-05; f =       132957.7997719
lambda = 1.6935e-05; f =        14164.0853306
lambda =  5.645e-06; f =          981.4360492
lambda = 1.8817e-06; f =         -477.9075493
lambda = 6.2723e-07; f =         -638.2668994
lambda = 2.0908e-07; f =         -655.7237468
lambda = 6.9692e-08; f =         -657.5952075
lambda = 2.3231e-08; f =         -657.7882902
lambda = 7.7435e-09; f =         -657.8071592
lambda = 2.5812e-09; f =         -657.8085086

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1430776.5085083
lambda = -2.0908e-07; f =       156703.4437925
lambda = -6.9692e-08; f =        16270.4510722
lambda = -2.3231e-08; f =         1043.6727975
lambda = -7.7435e-09; f =         -522.5699756
lambda = -2.5812e-09; f =         -654.7251630
Norm of dx 1.9126e+09
Predicted improvement:        0.088252280
lambda =          1; f =         -657.8077338
lambda =    0.33333; f =         -657.8085198
lambda =    0.11111; f =         -649.2152161
lambda =   0.037037; f =         -656.8584079
lambda =   0.012346; f =         -657.7044375
lambda =  0.0041152; f =         -657.7974648
lambda =  0.0013717; f =         -657.8074781
lambda = 0.00045725; f =         -657.8084830
lambda = 0.00015242; f =         -657.8085588
Norm of dx     2.0879
Predicted improvement:        0.000034946
lambda =          1; f =         -657.8085938
Norm of dx 0.00010395
Done for param e_a =   0.1445; f = -657.8086
Predicted improvement:        0.000012160
lambda =          1; f =         -657.8086060
Norm of dx 0.00017528
Done for param e_v =   0.4128; f = -657.8086
Predicted improvement:        0.000020161
lambda =          1; f =         -657.8086262
Norm of dx 3.3474e-05
Done for param e_rer =   0.0611; f = -657.8086
Predicted improvement:        0.000014237
lambda =          1; f =         -657.8086404
Norm of dx 5.3182e-06
Done for param delt =   0.0999; f = -657.8086
Predicted improvement:        0.000018641
lambda =          1; f =         -657.8086590
Norm of dx 0.00032678
Done for param sig =   2.0671; f = -657.8087
Predicted improvement:        0.000124776
lambda =          1; f =         -657.8087837
Norm of dx 0.00020517
Done for param hf =   0.7453; f = -657.8088
Sequence of univariate steps!!
Actual dxnorm 0.00051035
FVAL          -657.8088
Improvement   0.00023556
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.776699e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.44571 s.
 
Iteration 30
Correct for low angle: 7.71274e-09
Predicted improvement: 10839029.063131673
lambda =          1; f = 47376354812307.1640625
lambda =    0.33333; f = 5264038881322.4521484
lambda =    0.11111; f = 584893027892.4692383
lambda =   0.037037; f =  64988053441.5417099
lambda =   0.012346; f =   7220874182.9806318
lambda =  0.0041152; f =    802312084.7656155
lambda =  0.0013717; f =     89142976.6167585
lambda = 0.00045725; f =      9903450.7067116
lambda = 0.00015242; f =      1099554.3077596
lambda = 5.0805e-05; f =       121508.6670210
lambda = 1.6935e-05; f =        12891.7000103
lambda =  5.645e-06; f =          840.3590985
lambda = 1.8817e-06; f =         -493.4649148
lambda = 6.2723e-07; f =         -639.9565144
lambda = 2.0908e-07; f =         -655.9051443
lambda = 6.9692e-08; f =         -657.6134644
lambda = 2.3231e-08; f =         -657.7900986
lambda = 7.7435e-09; f =         -657.8074460
lambda = 2.5812e-09; f =         -657.8087433

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1424394.4218543
lambda = -2.0908e-07; f =       155998.1073184
lambda = -6.9692e-08; f =        16193.3416187
lambda = -2.3231e-08; f =         1035.5222924
lambda = -7.7435e-09; f =         -523.3360515
lambda = -2.5812e-09; f =         -654.7638786
Norm of dx 1.9083e+09
Predicted improvement:        0.001048592
lambda =          1; f =         -657.7968064
lambda =    0.33333; f =         -657.8079193
lambda =    0.11111; f =         -657.8088430
lambda =   0.037037; f =         -657.8088421
lambda =   0.071599; f =         -657.8088617
Norm of dx  0.0068472
Predicted improvement:        0.000021028
lambda =          1; f =         -657.8088828
Norm of dx 8.0735e-05
Done for param e_a =   0.1446; f = -657.8089
Predicted improvement:        0.000012560
lambda =          1; f =         -657.8088953
Norm of dx 2.3436e-05
Done for param e_g =   0.0542; f = -657.8089
Predicted improvement:        0.000011668
lambda =          1; f =         -657.8089070
Norm of dx  2.549e-05
Done for param e_rer =   0.0611; f = -657.8089
Predicted improvement:        0.000051881
lambda =          1; f =         -657.8089588
Norm of dx 1.0152e-05
Done for param delt =   0.0999; f = -657.8090
Predicted improvement:        0.000029613
lambda =          1; f =         -657.8089885
Norm of dx 0.00049602
Done for param phi1 =   1.4490; f = -657.8090
Predicted improvement:        0.000020245
lambda =          1; f =         -657.8090087
Norm of dx  0.0023581
Done for param phi2 =   5.4659; f = -657.8090
Predicted improvement:        0.000057637
lambda =          1; f =         -657.8090663
Norm of dx 0.00013922
Done for param hf =   0.7455; f = -657.8091
Predicted improvement:        0.000016851
lambda =          1; f =         -657.8090832
Norm of dx 0.00047376
Done for param rhov =   0.1799; f = -657.8091
Sequence of univariate steps!!
Actual dxnorm 0.0025191
FVAL          -657.8091
Improvement   0.00029948
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.901148e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.3108 s.
 
Iteration 31
Correct for low angle: 1.15712e-08
Predicted improvement:  7236254.677289396
lambda =          1; f = 72197374446988.1250000
lambda =    0.33333; f = 8021930003617.9970703
lambda =    0.11111; f = 891325392077.8286133
lambda =   0.037037; f =  99036099666.2770233
lambda =   0.012346; f =  11003992355.2233105
lambda =  0.0041152; f =   1222659195.1828361
lambda =  0.0013717; f =    135848431.8705390
lambda = 0.00045725; f =     15093024.4739802
lambda = 0.00015242; f =      1676205.0130021
lambda = 5.0805e-05; f =       185592.8649585
lambda = 1.6935e-05; f =        20016.0912436
lambda =  5.645e-06; f =         1634.0456722
lambda = 1.8817e-06; f =         -404.4814902
lambda = 6.2723e-07; f =         -629.8287215
lambda = 2.0908e-07; f =         -654.7230504
lambda = 6.9692e-08; f =         -657.4735321
lambda = 2.3231e-08; f =         -657.7740933
lambda = 7.7435e-09; f =         -657.8058922
lambda = 2.5812e-09; f =         -657.8089118

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1379137.2311412
lambda = -2.0908e-07; f =       150996.6070902
lambda = -6.9692e-08; f =        15646.6452214
lambda = -2.3231e-08; f =          977.7861086
lambda = -7.7435e-09; f =         -528.7507678
lambda = -2.5812e-09; f =         -655.0323689
Norm of dx 1.8779e+09
Predicted improvement:        0.000262213
lambda =          1; f =         -657.8084892
lambda =    0.33333; f =         -657.8091338
lambda =    0.11111; f =         -657.8091276
lambda =     0.2148; f =         -657.8091442
Norm of dx   0.013572
Predicted improvement:        0.000028278
lambda =          1; f =         -657.8091725
Norm of dx 0.00026738
Done for param e_v =   0.4132; f = -657.8092
Predicted improvement:        0.000014085
lambda =          1; f =         -657.8091866
Norm of dx 0.00028378
Done for param sig =   2.0664; f = -657.8092
Predicted improvement:        0.000041095
lambda =          1; f =         -657.8092277
Norm of dx 0.00011745
Done for param hf =   0.7458; f = -657.8092
Sequence of univariate steps!!
Actual dxnorm 0.0029481
FVAL          -657.8092
Improvement   0.00014454
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.879349e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.2646 s.
 
Iteration 32
Correct for low angle: 8.94706e-09
Predicted improvement:  9369220.149946747
lambda =          1; f = 40781507936951.3984375
lambda =    0.33333; f = 4531278235417.0791016
lambda =    0.11111; f = 503475217693.9355469
lambda =   0.037037; f =  55941643207.1422348
lambda =   0.012346; f =   6215721869.4246664
lambda =  0.0041152; f =    690629959.5795686
lambda =  0.0013717; f =     76734345.4898056
lambda = 0.00045725; f =      8524884.0367664
lambda = 0.00015242; f =       946442.3942837
lambda = 5.0805e-05; f =       104522.0946524
lambda = 1.6935e-05; f =        11013.8575128
lambda =  5.645e-06; f =          635.3867775
lambda = 1.8817e-06; f =         -514.9907556
lambda = 6.2723e-07; f =         -642.0340816
lambda = 2.0908e-07; f =         -656.0762540
lambda = 6.9692e-08; f =         -657.6229732
lambda = 2.3231e-08; f =         -657.7903648
lambda = 7.7435e-09; f =         -657.8076249
lambda = 2.5812e-09; f =         -657.8091699

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1334212.9058329
lambda = -2.0908e-07; f =       146032.2376728
lambda = -6.9692e-08; f =        15104.1221390
lambda = -2.3231e-08; f =          920.5325900
lambda = -7.7435e-09; f =         -534.1029485
lambda = -2.5812e-09; f =         -655.2906746
Norm of dx 1.8471e+09
Predicted improvement:        0.000112164
lambda =          1; f =         -657.8092510
lambda =    0.33333; f =         -657.8092802
lambda =    0.64439; f =         -657.8092888
Norm of dx  0.0017309
Predicted improvement:        0.000047870
lambda =          1; f =         -657.8093367
Norm of dx 0.00012187
Done for param e_a =   0.1448; f = -657.8093
Predicted improvement:        0.000011106
lambda =          1; f =         -657.8093478
Norm of dx 2.3573e-05
Done for param bet =   0.9194; f = -657.8093
Sequence of univariate steps!!
Actual dxnorm 0.0011223
FVAL          -657.8093
Improvement   0.00012014
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.979326e-20.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('panama.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m', 609)" style="font-weight:bold">panama.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+panama\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.22625 s.
 
Iteration 33
Correct for low angle: 9.05942e-09
Predicted improvement:  9272649.489524774
lambda =          1; f = 45563504291229.9531250
lambda =    0.33333; f = 5062611407171.2851562
lambda =    0.11111; f = 562512317944.4150391
lambda =   0.037037; f =  62501348067.9801788
lambda =   0.012346; f =   6944586983.1525393
lambda =  0.0041152; f =    771617977.9119036
lambda =  0.0013717; f =     85734015.7615338
lambda = 0.00045725; f =      9525180.9241645
lambda = 0.00015242; f =      1057697.2876707
lambda = 5.0805e-05; f =       116916.0992454
lambda = 1.6935e-05; f =        12400.4720268
lambda =  5.645e-06; f =          792.4558104
lambda = 1.8817e-06; f =         -496.8144599
lambda = 6.2723e-07; f =         -639.9695448
lambda = 2.0908e-07; f =         -655.8432762
lambda = 6.9692e-08; f =         -657.5962277
lambda = 2.3231e-08; f =         -657.7874013
lambda = 7.7435e-09; f =         -657.8074433
lambda = 2.5812e-09; f =         -657.8092703

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1418622.1026601
lambda = -2.0908e-07; f =       155360.2535742
lambda = -6.9692e-08; f =        16123.6296255
lambda = -2.3231e-08; f =         1028.1600790
lambda = -7.7435e-09; f =         -524.0277207
lambda = -2.5812e-09; f =         -654.7990611
Norm of dx 1.9045e+09
Predicted improvement:        0.000000395
lambda =          1; f =         -657.8093485
lambda =     1.9332; f =         -657.8093488
Norm of dx 7.1002e-06
Sequence of univariate steps!!
Try diagonal Hessian
Correct for low angle: 9.347e-09
Predicted improvement:   267457.634917105
lambda =          1; f =  37906972466.0113754
lambda =    0.33333; f =   4211880060.6504259
lambda =    0.11111; f =    467984367.9838828
lambda =   0.037037; f =     51997112.1824917
lambda =   0.012346; f =      5776690.8102264
lambda =  0.0041152; f =       641215.9262281
lambda =  0.0013717; f =        70645.5742502
lambda = 0.00045725; f =         7261.0298602
lambda = 0.00015242; f =          221.6614498
lambda = 5.0805e-05; f =         -560.2038125
lambda = 1.6935e-05; f =         -647.0020585
lambda =  5.645e-06; f =         -656.6210840
lambda = 1.8817e-06; f =         -657.6814566
lambda = 6.2723e-07; f =         -657.7964732
lambda = 2.0908e-07; f =         -657.8083185
lambda = 6.9692e-08; f =         -657.8093233
lambda = 2.3231e-08; f =         -607.7763569
lambda = 7.7435e-09; f =         -654.6743301
lambda = 2.5812e-09; f =         -657.5026353

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =          320.2236477
lambda = -2.0908e-07; f =         -588.8520003
lambda = -6.9692e-08; f =         -657.3899983
lambda = -2.3231e-08; f =         -640.8213305
lambda = -7.7435e-09; f =         -655.5144483
lambda = -2.5812e-09; f =         -657.5301685
Norm of dx 5.4932e+07
Try gradient direction
Predicted improvement:        0.000189656
lambda =          1; f =         -657.7904162
lambda =    0.33333; f =         -657.8073538
lambda =    0.11111; f =         -657.8091563
lambda =   0.037037; f =         -657.8093369
lambda =   0.012346; f =         -657.8093506
Norm of dx 0.00019476
No further improvement is possible!
Actual dxnorm 1.407e-05
FVAL          -657.8094
Improvement   2.7861e-06
Ftol          1e-05
Htol          1e-05
Gradient norm  1.9476
Minimum Hessian eigenvalue 3.137e-14
Maximum Hessian eigenvalue 3845385.5876
Estimation successful.

Final value of minus the log posterior (or likelihood):-657.809351 

RESULTS FROM POSTERIOR ESTIMATION
parameters
       prior mean     mode    s.d.  prior pstdev

alp        0.3300   0.3343  0.0198   norm 0.0200 
bet        0.9450   0.9194  0.0131   unif 0.0260 
delt       0.1000   0.0999  0.0010   norm 0.0010 
sig        2.0000   2.0653  0.0947   norm 0.1000 
phi1       1.5000   1.4497  0.0972   norm 0.1000 
phi2       5.6000   5.4687  0.4832   norm 0.5000 
psi1       1.4000   1.4000  0.5000   norm 0.5000 
hf         0.5000   0.7460  0.0354   beta 0.2000 
rhoa       0.7000   0.4083  0.0947   beta 0.2000 
rhov       0.5000   0.1796  0.0987   beta 0.2000 
rhog       0.5000   0.5970  0.0892   beta 0.2000 
rhorer     0.0000   0.5017  0.1095   unif 0.5774 
rhoyw      0.5500   0.5528  0.0733   beta 0.1000 

standard deviation of shocks
       prior mean     mode    s.d.  prior pstdev

e_a        0.0100   0.1448  0.0217   invg    Inf 
e_v        0.0100   0.4132  0.0508   invg    Inf 
e_g        0.0100   0.0542  0.0054   invg    Inf 
e_rer      0.0100   0.0611  0.0102   invg    Inf 
e_yw       0.0100   0.0098  0.0008   invg    Inf 


Log data density [Laplace approximation] is 611.473509.

Estimation::mcmc: Multiple chains mode.
Estimation::mcmc: Searching for initial values...
Estimation::mcmc: Initial values found!

Estimation::mcmc: Write details about the MCMC... Ok!
Estimation::mcmc: Details about the MCMC are available in panama/metropolis\panama_mh_history_0.mat


Estimation::mcmc: Number of mh files: 1 per block.
Estimation::mcmc: Total number of generated files: 2.
Estimation::mcmc: Total number of iterations: 20000.
Estimation::mcmc: Current acceptance ratio per chain:
                                                       Chain  1: 29.035%
                                                       Chain  2: 29.025%
Estimation::mcmc: Total number of MH draws per chain: 20000.
Estimation::mcmc: Total number of generated MH files: 1.
Estimation::mcmc: I'll use mh-files 1 to 1.
Estimation::mcmc: In MH-file number 1 I'll start at line 10001.
Estimation::mcmc: Finally I keep 10000 draws per chain.

marginal density: I'm computing the posterior mean and covariance...  Done!
marginal density: I'm computing the posterior log marginal density (modified harmonic mean)... Done!


ESTIMATION RESULTS

Log data density (Modified Harmonic Mean) is 611.359963.
parameters
         prior mean   post. mean        90% HPD interval    prior       pstdev

alp           0.330       0.3337      0.3034      0.3624     norm       0.0200
bet           0.945       0.9219      0.9022      0.9385     unif       0.0260
delt          0.100       0.0999      0.0983      0.1015     norm       0.0010
sig           2.000       2.0733      1.9168      2.2303     norm       0.1000
phi1          1.500       1.4412      1.2832      1.6020     norm       0.1000
phi2          5.600       5.5456      4.8103      6.3086     norm       0.5000
psi1          1.400       1.3884      0.5881      2.2252     norm       0.5000
hf            0.500       0.7508      0.6931      0.8111     beta       0.2000
rhoa          0.700       0.4063      0.2413      0.5560     beta       0.2000
rhov          0.500       0.2017      0.0465      0.3407     beta       0.2000
rhog          0.500       0.5844      0.4403      0.7193     beta       0.2000
rhorer        0.000       0.4805      0.3080      0.6646     unif       0.5774
rhoyw         0.550       0.5550      0.4385      0.6648     beta       0.1000

standard deviation of shocks
         prior mean   post. mean        90% HPD interval    prior       pstdev

e_a           0.010       0.1569      0.1156      0.1953     invg          Inf
e_v           0.010       0.4475      0.3549      0.5414     invg          Inf
e_g           0.010       0.0577      0.0481      0.0676     invg          Inf
e_rer         0.010       0.0682      0.0485      0.0880     invg          Inf
e_yw          0.010       0.0100      0.0086      0.0114     invg          Inf
Estimation::mcmc: Posterior (dsge) IRFs...
[Warning: Exported image displays axes toolbar. To remove axes toolbar from image, export again.] 
Estimation::mcmc: Posterior IRFs, done!
Estimation::compute_moments_varendo: I'm computing endogenous moments (this may take a while)... 


Posterior mean variance decomposition (in percent)
          e_a     e_v     e_g   e_rer    e_yw
y       79.63    9.98    9.45    0.92    0.02
x       60.96   38.68    0.33    0.03    0.00
c       60.01   39.10    0.83    0.06    0.00
w       98.31    1.53    0.15    0.01    0.00
R        6.67    0.87   85.65    6.60    0.21
k       63.93   35.55    0.48    0.04    0.00
d        3.88    0.44   87.13    8.33    0.21
r       52.44   42.70    4.44    0.41    0.01
l       96.65    1.77    1.44    0.14    0.00
la      59.54   40.01    0.41    0.04    0.00
tb      27.55    3.36    3.18   64.27    1.64
a      100.00   -0.00    0.00   -0.00    0.00
v        0.00  100.00    0.00    0.00    0.00
g        0.00    0.00  100.00    0.00    0.00
rer      0.00    0.00    0.00  100.00    0.00
yw       0.00    0.00    0.00    0.00  100.00


Done!

Estimation::mcmc: Smoothed variables
[Warning: Exported image displays axes toolbar. To remove axes toolbar from image, export again.] 
[Warning: Exported image displays axes toolbar. To remove axes toolbar from image, export again.] 
Estimation::mcmc: Smoothed variables, done!
Estimation::mcmc: Smoothed shocks
Estimation::mcmc: Smoothed shocks, done!
Estimation::mcmc: Trend_coefficients
Estimation::mcmc: Trend_coefficients, done!
Estimation::mcmc: Smoothed constant
Estimation::mcmc: Smoothed constant, done!
Estimation::mcmc: Smoothed trend
Estimation::mcmc: Smoothed trend, done!
Estimation::mcmc: Updated Variables
Estimation::mcmc: Updated Variables, done!
Total computing time : 0h07m35s
Note: warning(s) encountered in MATLAB/Octave code
